recursal/Fanatic-Fandom huggingface dataset:
Research Design

Exploratory - To find out more about the research question, background info, establish research priorities, clarify problems and hypotheses. Primary data gathering or Secondary data gathering.

Descriptive - To describe and measure marketing phenomena. WHO WHAT WHEN WERE WHY HOW.

* Cross section = snapshot of a group of people in a single point in time
* More representative of pop'n
* Cheaper
	+ Single = only one group of people in snapshot
	+ Multiple = multiple group of people in a snapshot
* Longitudinal = continuous recording of the same group of people
* Can see change over time
* Large amount of data
* Have to account for questionnaire fatigue
* Have to account for people dropping out
	+ Continuous panel = same questions
	+ Discontinuous panel = different questions

Causal - To determine causality. Need Experiments. Control and Intervention group. Confounding variables accounted for. Control and Intervention group need to have statistically negligible differences/be considered statistically similar.

Research Design branches:

* Research Design - Exploratory or Conclusive:
	+ Conclusive design - Qualitative or Quantitative
	+ Exploratory design - Descriptive or Causal
		- Descriptive design - Cross Sectional or Longitudinal
			* Cross Sectional design - Single Cross Sectional or Multiple Cross Sectional
Stratified Sampling

Divide the population into strata according to a feature of a population. Then take a simple random sample from each strata. Each of the samples are taken independently.

Ideally, variation between strata is large but variation within strata are small. Heterogenous between but homogenous within. This would help in the accuracy of the

H is the letter used to denote the strata. Capital N with subscripts from 1 to H denote the number of population units in the strata. Small n with subscripts 1 to H denotes the samples taken from the strata.

sum of samples taken from strata = overall sample size

sum of strata = overall population

Why stratified sampling?

* More representativeness
* More precision
* Study specific subpopulations
* To assist in implementing operational aspects of survey research

Estimation strategy

* Think Logically. Think slow. Not too complicated.
* When using proportions, treat proportions as means
* Total estimate for each stratum can be calculated using proportions(ph) as Nhph
* Can add the estimate for each stratum to get total estimate
* Total variation is just addition of the variables for each strata
	+ sampling from each strata is independent so they can be added
* Nh/N is weight.

Allocation of population to strata

* Equal Allocation
	+ when all stratas have the same number drawn from the population
* Proportional Allocation
	+ nh/Nh = Nh/N
* Allocation to produce estimates for subpopulations
* Optimal Allocation
	+ http://stattrek.com/statistics/dictionary.aspx?definition=Neyman\_allocation
	+ When we want to maximise survey precision
Discriminant Analysis

Like regression but for when the dependent variables are categorical variables

http://stats.idre.ucla.edu/spss/output/discriminant-analysis/

Statistics associated with discriminant analysis

* Canonical Correlation
	+ The extent of association between discriminant scores and groups
* Centroid
	+ Mean value of the discriminant scores for a particular group
* Classification Matrix
	+ Contains number of correctly predicted cases
* Discriminant Function Coefficients
	+ Multipliers of variables when the variables are in the original units of measurement
* Discriminant Scores
	+ Unstandardised coefficients multiplied by variable values. Products are summed and added to constant term.
* Eigenvalues
	+ The ratio of the within-group sum of squares and the between-group sum of squares
	+ How much discriminating ability a function has
	+ The larger the better
* F Values and their Significance
	+ Calculated from one-way ANOVA with the grouping variable serving as the categorical independent variable
* Group means and their standard deviations
	+ Computed for each predictor for each group
* Pooled within group correlation matrix
	+ Average of separate covariance matrix
* Standardised discriminant function coefficients
	+ When the coefficients have been standardised to have a mean of 0 and variance of 1
* Structure coefficients
	+ Simple correlations between predictors and discriminant function
* Total correlation matrix
	+ If the cases are treated as if they were a single sample and correlations were computed
* Wilk's Lambda
	+ the ratio of the within-group sum of squares means and the total sum of squares
	+ Large value means that there is little difference between the means
	+ Small value means there is a difference between the means

Discriminant Analysis

* Formulate Problem
	+ estimation/analysis sample used to estimate discriminant function
	+ holdout/validation sample left out for later validation
* Estimate the different function coefficients
* Determine significance of discriminant function
* Interpret results
* Assess validity of discriminant analysis
	+ Use holdout/validation sample
	+ Find hit ratio, the percentage of cases correctly classified
	+ Classification accuracy should be at least 25%

Stepwise Discriminant Analysis -

* Forward - F ratio calculated for every variable one by one and the ones that meet the cutoff are added in one by one
* Backward - All variables added in and all the F ratios calculated. Then the variables not meeting the cutoff are taken out one by one.
Game Theory

What would I do if he does that?

Look forward and reason back.

Players are RATIONAL. They will try to maximise their own gains.

In a Nash Equilibrium: It is a set of strategies such that both players and playing their best response, there is no incentive to deviate and is the only possible combination of strategies.

Dominant strategies are played regardless of whatever the other player is playing.

Weakly dominant strategies are strategies that are no worse off from being played by the player. It is as at least as good as any other strategies.

Dominated strategies have no reason to be chosen because there exists a strategy that is strictly better than it.

In pure strategy there is no probabilities of strategies being played or not. They are either chosen or not.

In a mixed strategy game the strategies have probabilities of being played. When solving questions: Players need to feel indifferent between the strategies being played p\*payoff1 + (1-p)\*payoff2 = p\*payoff3 + (1-p)\*payoff4. Find the intersection by drawing a graph for the NE.

Sequential games. Players play strategies one after the other. Look forward to the future for the ideal result/payoff for yourself and reason back to your original position anticipating what the other player will do.

a sequential game where there is an incentive to deviate: payoff\*[discount rate/(1-discount rate)]

a strategic option is credible, observable and irreversible

Pure Strategy: A ***complete contingent plan of action*** that specifies an action that a player would choose under any contingency the player may face in a game

Dominant Strategy: A strategy **has to outperform every other strategy, strictly higher payoff**, no matter the strategy played by the other player.

Nash strategy are predictions of what the players will play if they are rational.

Pure strategy subgame perfect nash equilibria: A profile of strategy that **constitutes a nash equilibrium for every subgame of a game**
Multiple Regression

Adding more explanatory variables to the regression model so that there can be more accurate models.

k is the number of regression variables

Adjusted R^2

* R^2 becomes less useful as more variables are added
* The gap between R^2 and adjusted R^2 as non-significant independent variables are added to the regression equation
* A good model would have R^2 and adjusted R^2 to be quite close around 2-3%

Regression Assumptions - still the same -> NICE-L

Significance Testing

* Check the estimated standard deviation. Estimated standard deviation of the model can be read as standard error which is a square root of the residual mean squared
* Run a F test to examine model with the null being that the model has no predictability while the alternative being the model has predictability.
	+ Null not having predictability means that If null is failed to be rejected, that means the model is useless.
	+ This is a test for overall significance. For individual variables testing, t test is used.
* Run a t test on the coefficients of individual variables.
	+ Can run a hypothesis test with null being coefficient is zero and alternative being coefficient is not to see which variables are useful to the model or not.

Residual analysis

* Residual plotting
	+ Plot the residuals against each independent variable
	+ A random plot is a good sign. Anything else is a problem.
	+ Include a quadratic term or taking a log of the dependent variable
* Histogram
	+ Histogram of residuals may show skewness in the residuals
	+ A good histogram of residuals shows rough normality or approximate symmetry
	+ Skewness is bad
* Normal probability plot
	+ An ideal normal probability plot should be at least 45 degrees
	+ Anything other is bad
* Homoskedasticity and Heteroskedasticity
	+ Can be found by plotting residuals against the fitted (y hat) values
	+ A cone shape is heteroskedasticity and is bad
	+ A blocky, amorphous shape is homoskedasticity and is good.
Information and Value Creation

The agent with more information always benefits.

Quality can be observable or unobservable. When quality is observable, each high quality and low quality is sold for the desired amount by the suppliers.

But when quality is unobservable, the market price and the expected value to the customer becomes mismatched.

Expected value to customer Qh/(Qh+Ql)\*Ph + Ql/(Qh+Ql)\*Pl

Always substitute value into above. The equation above is what you will come back to always.

When information is not perfect, there is a deadweight loss always. There is a limit to which the suppliers of high and low will supply. If the market price/equilibrium price does not match the actual value of the products, less or more will be supplied.

The deadweight loss is calculated by deltaQ\*deltaP\*1/2. deltaQ is the difference between the quantity supplied if the price equals the true value minus the quantity actually supplied. deltaP is the difference between the desired price and the actual market price. Also known as market inefficiency and market failure.

There is such thing as signalling to reduce market information asymmetry. Sellers try to make it known about their products more through advertising, warranties, returns etc. This is a costly action so as to prevent undervaluing of their products through imperfect information. Firms can also have a good reputation of quality through various means one of them being branding. User generated reviews are another example of trying to solve imperfect information.
Alternative Sampling Techniques

Unequal Probabilities

* Reasons for sampling with unequal probabilities
	+ Disproportional stratification(due to one subset of population being larger than the other for instance)
	+ Multistage sampling
	+ PPS sampling

Multistage

* One type of sampling method in first stage eg: Cluster Sampling
* Do another method of sampling in the next stage of sampling
* So on and so forth as sampling design requires
* Calculating probability of selection is just multiplication of each probability of selection at each stage together

Probability Proportional to Size(PPS) Sampling

* The probability of a sample being selected is proportional to the size variable in the population(pop'n 60 has 40 of x so 40/60 = 2/3 chance of x being selected)
* In practice PPS is done without replacement usually. PPS can also be done with replacement sampling.
* PPS sampling better in SRS in terms of variance
* PPS total estimate = t(est) = 1/n summation sample/probability of selection
* E(tpps(est)) is unbiased. Take the 1/n and summation outside of E() because has no i. Summation of sample/probability of selection = t therefore unbiased.
* For PPS, the t(est) is the same for all.
* Constant of proportionality k = n/Sigma(M).
* n is sample size.
* M is size of the variable in population.
* Sigma M would be the total size of the variable in the population
* The probability of selecting a variable is thus kM. Constant of proportionality \* Size measure.
History

History est le 3ème épisode de la web-série dans Wolfblood Secrets qui a été diffusé le 5 Octobre 2016, au Royaume-Uni.

## Résumé (A vérifier)

Jones utilise des témoignages de Mr. Jeffries et d'Imara Cipriani pour contester la connaissance de Jana Vilkas de l'histoire des Wolfblood. Alors qu'Imara prétend que les humains et les Wolfblood, une fois combattu côte à côte, Mr. Jeffries est flatté en exposant sa théorie que certaines des figures les plus redoutées dans l'histoire étaient en fait des Wolfblood. Smith commence à se demander si Jana Vilkas veut que l'histoire se répète et souhaite laisser son propre héritage effrayant.

## Personnages apparus

* Leona Kate Vaughan - Jana Vilkas
* Michelle Gayle - Imara Cipriani
* Mark Fleischmann - Mr. Jeffries
* Simon Trinder - Smith
* Samantha Power - Jones
General Stats Notes

**Also wrong answer notes**

Write down the topic to trigger the memory

Precision is increased as sample size increases. Inversely proportional to square root of n.

Bias would not change due to sample size if sample estimator is an unbiased estimator of population variable.

In non-probability sampling, the probability of sampling a unit is not equal for each unit so statistical methods can't be applied

Randomisation allows a causal relationship to be concluded from the data

***USE THE FORMULA BOOK***

Bias is systematic error

Proportional allocation is proportional to stratum size

Neyman allocation is proportional to stratum standard deviation size

If stratum standard deviation varies a lot, Neyman allocation is advantageous

S = population standard deviation. s = sample standard deviation.

For standard error of total, multiply N to the standard error.

In stratified sampling, the variation between strata is not counted for.

Just use the std deviation given, doesn't matter what, for Neyman allocation. No need to adjust.

Ratio estimator there is some error/bias in smaller samples.

X, Y and Z in randomisation, causation and experiments

Write the formula down for 1 mark

Write down the calculation even if putting it in the calculator

When they ask precision, they want variance

Get used to cluster sampling. Define what each of the notatin mean in each question.

As long as you clearly show the steps, the question will be given marks even if there is little error.

standard deviation measures variability of random variable

standard error is the standard deviation of the distribution of the sampling distribution of estimator

sampling error is due to random variability during the sampling process

non-sampling error is due to failure of the sampling scheme

If there is proportionality in the data, ratio estimators are preferred

Say what the symbols mean

Use tables when calculating to organise stuff

Cluster sampling and Ratio Regression and Estimation often overlap
Tailor Expansion

Tailor Expansion is an approximation of a function

F(t) at t = 0 is approximated as

F(0) + F'(0)t + F''(0)t^2/2! + F'''(0)t^3/3!.....

We usually calculate until second derivative as the higher derivatives are more

At classification of stationary points, the first derivative is canceled out as stationary points are equal to when F'(t) = 0 as a result: F(0) + F''(0)t^2/2!

At a certain point x = a, the Tailor expansion is

F(0) + F'(0)(x-a) + F''(0)(x-a)^2/2! + F'''(0)(x-a)^3/3!.....

The quadratic term if negative shows that at the point the function has a maximum. If positive then it's a minimum.

Convex and Concave functions

When F''(x) > 0 for all x, the function is convex on the interval. Convex function lies on or above all the tangent lines. If convex has a local minimum at x = a, it is a global minimum.

When F''(x) < 0 for all x, the function is concave on the interval. Concave function lies on or below all the tangent lines, If a concave has a local maximum at x = a, it is a global maximum.
Correlation + Regression

Correlation =/ Causation

Correlation == Related to one another

Causation == One causes another

(UNFINISHED)

Regression

* Simple Linear Regression - single explanatory variable regression
	+ Also known as bivariate regression analysis
* Multiple Regression - multiple explanatory variables exist in the regression
Optimisation of function of n variables

Second degree (quadratic) Taylor approximation

del/nabla = upside down delta

del/nabla = gradient

f(x) = f(a) +  delf(a)\*(x-a) + 1/2\*(x-a)^T\*f"(a)\*(x-a)

When finding stationary points, the second bit disappears like before

f(x) = f(a) + 1/2\*(x-a)^T\*f"(a)\*(x-a)

Classifying the stationary point requires a Hessian, a matrix of second derivatives

Find the stationary points from first derviatives

Put points into Hessian. Get the eigenvalues. If all negative = maximum. If all positive = minimum.

You need to look at the e-values.

If f"(a) > 0, positive semidefinite. Surface lies above tangent plane. Convex. a is global minimum.

If f"(a) < 0, negative semidefinite. Surface lies below tangent plane. Concave. a is global maximum.

Principal minors have to be used to classify maximum or minimum. ++++... and -+-+... is the only combos you care about. +++ is min and alternate is negative. All other is indefinite.

put second derivatives into matrix

substitute points into matrix

find det of matrix

if zero then undefinable

if negative then saddlepoint

if positive then stationary point

principal minor to find nature of stationary point

positive min negative max
Stepwise modelling, Missing Values, Model Validation (and more)

Stepwise modeling

* Forward; Nothing in model, add variables to model if they are significant, add one by one, stop adding when all significant variables are added
* Backward: Everything in model, take away variables in model if they are insignificant, take away one by one, stop taking away when the remaining variables are significant
* Good for exploratory and initial stages of research
* Generally, produces the most plausible and good model
* Order at which variables are added/taken away doesn't matter
* Forward/backward may give different regressions and may be confusing
* Among the many combinations of variables in a regression, how to choose:
	+ https://en.wikipedia.org/wiki/Mallows's\_Cp
	+ Select the model with the fewest variables having Cp approximately equal to p with p variables and n datapoints
	+ Mindless but simple
	+ Too many calculations, tedious, inefficient, overwhelming
	+ Best model will be included in the list

Missing values

* Values can be missing or erroneous for a variety of reasons(Non-response section in ST205)
* Do what is reasonable to make up for the missing/erroneous values. No hard and fast rules.

Model Validation

* Check if variables included seem reasonable eg: sign of coefficient, size, etc
* Find out if model can predict new data well. Assess prediction errors. They should have zero mean, no pattern, low variance.
* Use part of data to create model then use the model to predict the remaining data not used
Experiments

Control group exists

Intervention group exists

Both groups have statistically insignificant/negligible differences. Allocation of control and intervention is randomised.

Randomisation allows a causal relationship to be concluded from the data

X treatment, Y outcome, Z confounders

Z are a problem because they obfuscate the effect of X

Randomisation breaks link between X and Z to allow Y to be measured solely through effects of X

Randomisation also allows the control and treatment to be same on average

There exists a null hypothesis which can be disproven.

There can be a simple cross section experiment design with no followup. There can be one or two followups to an experiment to see the changes to the participants.

* Specify research objectives
* Consider ethical issues
* Specify further(how to measure and intervene)
* Determine sample selection
* Determine data collection
* Consider budget and time scales
* Determine experiment design
* Recruit interviewers
* Pre test to test measurement methods
* Implement intervention and data collection
* Data analysis
* Final Report
* Specify targe pop'n, analysis & sampling units, variable to consider
* Consider ethical issues
* Specify sampling frame and dat collection methodology
* Design questionnaire
* Determine sampling design
* Recruit and train interviewers
* Pilot survey
* Main survey data collection
* Consider nonresponse
* Data analysis
* Final report

Data collection methods

* Computer(interview, self-interview, telephone, surveys)
* Mail
* Telephone
* Personal Interview

Nonresponse

* Types
	+ Unit nonresponse - nonresponse for the entire survey
	+ Item nonresponse - nonresponse for one question or a subset of questions
* Sources
	+ Refusal
	+ Inability
	+ Fatigue
	+ Unavailability
	+ Non-contact
	+ Mistake/accident
* Adjusting for nonresponse
	+ Weighting
	+ Imputing
	+ Followup
	+ Incentives
	+ Substitution

* Result: Nonresponse bias, inaccurate survey result and generalisation
Entry and Exit

Entry and Exit in Industries

* Entry increases competition
* Competition forces out inefficient firms
* Entry and exit are highly correlated
* Firms can affect entry barriers. Number, size, etc

Entry Decisions in and Barriers to Entry

* Entrant can be new firm or established firm in another industry
	+ Can be strategic or structured
	+ Strategic is what incumbents do
		- Strategic blocking must be profitable for incumbent to do
		- Must change entrant's expectations, post-entry profits
		- Process innovation
		- Limit Pricing - setting a low price
		- Predatory Pricing - setting an extremely dangerously low self-damaging price
		- What these firms do is signalling. They can signal to entrants that they will take action and if the threat is credible enough the entrant will not enter with the incumbent doing nothing.
		- Incumbents can signal jam as in pretend to be threatening but entrant can always see through this logic.
	+ Structured is natural advantages and intrinsic product characteristic or technology
		- Control of essential resources(natural resources, patents, etc)
		- Economies of scale and scope(cutting costs a lot)
		- Marketing advantages of incumbency(umbrella branding
* Entry conditions are: Blockaded, Accommodated, Deterred
* A new competitor entering the market reduces the incumbent's profits and market share so the incumbent has an incentive to keep the competitor out.
* Compare post-entry profit and pre-entry profit for the incumbent. Have to take into account of efforts(cost) to of blocking entry in this comparison.
* New entrant has to take into account of initial investment to get into the market. Want profits post-entry to cover the costs of investment to make entry worthwhile.
	+ Entrants take into account of post-entry profit and competition
* If Profit gained after entry >= Investment to get in then the new competitor will enter. If not then stay out.
* Sometimes better to let the entrant in. If blockaded profit < Accommodated profit then let in. Blocking to make entrant stay out may be more expensive/costly than letting the entrant in.

Equilibrium Market Structure
Stationary Points of Quadratic Functions

Get partial derivatives in terms of x and y and z and etc

Make it equal to zero and find answer

The determinant of the matrix when calculating the answer(just the xyz,etc) part can be used to see if the stationary point is unique

This is the stationary point

Classifying the stationary point:

The equation can be made into matrix form using the quadratic portion of the equation. x^tAx like from before. A is a symmetric matrix. Use principal minor of A to find if point is positive definite. If positive definite then there can be a stationary point. If det of A is > 0 then minimum. If det A < 0 then maximum.

ab - c^2 > 0 minimum

ab-c^2 < 0 maximum

Can be applied to profit maximisation for firms with two products

Same as above just applied to this setting

Remember to multiply the prices by the quantities

Add the two revenues and take away the cost

Differentiate by both x and y and find the optimal point.

Classify the point.
Trevor Cooper

Trevor Cooper joue le rôle du Grand-père de Katrina MacKenzie dans la série Wolfblood.

Il est né à Londres, en Angleterre.

## Films

* 1981: Lady Killers - Oliver
* 1984: Diana - Harrington
* 1985: Docteur Who - Takis
* 1986: Mr Pye - Charlie
* 1987: Star Cops - Colin Devis
* 1988: Theatre Night - John Bulgin
* 1990: Stay Lucky - Barry Kernon
* 1991: Kinsey - Mo
* 1991: Drop the Dead Donkey - Bill
* 1982 - 1991: Minder - Derek
* 1992: Love Hurts - Andrews
* 1992: Perfect Scoundrels - Larry Gill
* 1989 - 1922: Boon - Bernie Smith
* 1993: Gallowglass - Stan
* 1993: Frank Stubbs Promotes - Archie Nash
* 1986 - 1995: Casualty - Eddie McCann / Ralph
* 1984 - 1996: The Bill - Kerry Durnin / Frederick Cotterell / Tony Lubbock
* 1997: Insiders - Jimmy Kerr
* 1999: Days Like These - Ron Foreman
* 1999: Inspecteurs associés - Geordie Turnbull
* 2000: Longitude - Roger Wills
* 2000: Heartbeat - John Oakes
* 2003: Inspecteur Barnaby - Sean Moorcroft
* 2003: Trevor's World of Sport - Phil
* 2004: Down to Earth - Mr. Cowley
* 2006: Tripping Over - Mr. Robinson
* 2007: Murphy's Law - Clive Salter
* 2008: New Tricks - Malcolm Hagley
* 2013: Vikings - Earl Bjarni
* 2005 - 2014: Holby City - Jeffrey Moore / Bernard Wesson / Jimmy Chapman
* 2006 - 2014: Doctors - Jacob Ware / Martin Mansfield
* 2016: Boomers - Chris
* 2017: Wolfblood - Grand-père de Katrina MacKenzie
Horizontal Mergers

Horizontal Merger - when the acquired firm uses both the same input and output market

Two main reasons for horizontal merging:

* Efficiency
* Internalize externalities/increase market power

Efficiency Mergers

* Methods: Economies of Scale, Increased Purchasing Power with Suppliers, Leveraging Brand Name/Core-Competency/Reputation, One-stop shopping to reduce customer costs, Reducing waste/off-peak capacity/efficient use of waste
* Common ownership is preferred over joint operation and separate ownership because it reduces transaction(information and coordination) costs and opportunism
* Mergers are a bad news for competitors overall.

Diversification

* Mergers that do not share same input or output markets is called unrelated diversification
* Unrelated diversifications make conglomerates
* Reasons for profitable diversification:
	+ Undervalued market
	+ External capital markets = have access to better capital
	+ Internal capital markets = allocate capital more efficiently
	+ Dominant General Management Market = skills from management applicable in other areas
* Why merger can be preferable to growth
	+ Compensation tied to size of firm
	+ Larger firms have more social power, political power, reputation
	+ Larger firms have better private cash flows
* Diversification reasons that are suspect
	+ Diversification and risk = shareholders can diversify by diversifying portfolio not necessarily diversification
	+ Identifying Undervalued Firms = how would a manager identify an undervalued firm?

Market for Corporate Control

* Shareholders have to try to reign in managers from diversifying too much
* They have weak incentive to monitor management so need other methods

Performance of Conglomerates

* Long-term performance of diversified firms tend to be poor
* The individual parts perform better than a whole for diversified firms
* Diversification depends more on the external environment
* Conglomerates are decent
Sampling size determination

Finite Population Correction(FPC) = correction for the overestimation of the variance of a population parameter. When n >= 0.1N. FPC is sqrt[(N-n)/(N-1)]. Have to multiple standard deviation by this to adjust.

Sampling Distribution = distribution of sample statistic values computed for each possible sample which could be drawn from the target population under a specific sampling scheme

Confidence intervals are supposed to cover or span the true population parameter

Incidence rate is the rate of occurrence or percentage of persons eligible for the study

Completion rate is the number of eligible people who complete the survey itself.

Initial Sample Size = Final Sample Size / (Completion Rate \* Incidence Rate)

Adjusting for Nonresponse

* Adjusting for nonresponse can be done through = imputation, weighting, replacement, substitution, past data(trend), subjective(researcher) estimate
* Reducing Refusals
	+ Easy questions
	+ Short questionnaires
	+ Pilot tested questionnaires
	+ Prior notification
	+ Incentives
	+ Follow-up
* Reducing Not at Homes
	+ Contacting people during off hours
	+ Using methods other than phone
	+ Follow-up
	+ Call back
Matrix Rank

Row Echelon Form: diagonal 1s from top left to bottom right with bottom part of diagonal being zeros and top part being any number. (http://mathworld.wolfram.com/EchelonForm.html)

Rank of Matrix: how many non zero rows there are after echelon form has been calculated.

Ax = 0 can be easily solved using the reduced REF. Can find x in terms of arbitrary values(eg: a & b) which means there is an infinite number of solutions of x. Called a ***solution space***.

This is a general solution.

In matrix m x n, m is columns and n is rows. r = rank of matrix.

If r < n,

When Ax = b (a non zero vector), the solution is the particular solution to Ax = b and the general solution of Ax = 0. This is x = p + v.

p is the particular solution to Ax = b, v is the general solution to Ax = 0.

Suppose matrix A is m x n with rank r

if r = n, there exists a unique solution

if r < n, there exists an infinite number of solutions
La Comète

La Comète est le 8ème épisode de la Saison 3 de la série Wolfblood sur Disney Channel, qui a été diffusé pour la première fois le 28 Mars 2015.

## Résumé

Ce soir, tous les élèves regardent une comète dans le ciel pour le cours de sciences. Les Wolfblood ignorent les effets que la comète pourrait avoir sur eux.
MG301

A mix of quant and qual

3-4 sentences max for qual questions. Succinct and to the point.

They will ask you the same questions for qual, ***nothing unexpected***, so practice the questions you already got. MEMORISE, PRACTICE, REPEAT.

Wrong Answer Notes MG301

Topics:

Game Theory

Market Structure: Monopoly, Oligopoly, Perfect Comp

Entry and Exit

Industry Analysis

Competitive Advantage: Innovation

Cost and Benefit Advantage: Hotelling, Quality differentiation

Focus Strategies and Niche Markets

Information and Value Creation(ie Information Asymmetry)

Economic View of Organisation

Pay for Performance

Incentives in Teams

Decentralisation

More Decentralisation (Delegation of decisions/work and communication)

Even More Decentralisation (Knowledge Specialisation)

Horizontal Mergers

Vertical Mergers (Make vs Buy, Adaptation and Rent/Quasi-rent)

Make vs Buy (Property Rights and Incentive System)
Samantha Power

Samantha Power joue le rôle de l'Agent Jones dans la web-série de Wolfblood Secrets.

## Films

* 1997 - 1998: A Prince Among Men - Sonia Trent
* 2000: Médecins de l'ordinaire - Christine Lynch
* 2000: City Central - Liz Gardner
* 2001: Where the Heart Is - Réceptionniste
* 2002: The Safe House - Femme de ménage
* 2003: Barbara - Jane
* 2005: The Royal - Hazel Barton
* 2005: Twisted Tales - Kelly
* 2006: New Street Law - Tina Bennett
* 2004 - 2006: Little Britain - Jane
* 2008: The Cup - Debbie Rossi
* 2009: Shameless: Very Important Punk - Helen
* 2009: Heartbeat - Lynne Millwood
* 2009: Lunch Monkeys - Chantelle
* 2010: Moving On - Lynnie
* 2011: Waterloo Road - Sarah Pearson
* 2012: Starlings - Samantha
* 2012: In with the Flynns - Amy
* 2012: Crime Stories - Tracy Watts
* 2013: Prisoners Wives - Candice
* 2013: The Mimic - Danielle
* 2014: Holby City - Sophie Walker
* 2014: All at Sea - Mrs. Brown
* 2015: Ordinary Lies - Tanya
* 2015: 4 O'Clock Club - Mrs. Thompson
* 1995 - 2015: Coronation Street - Talisa Grady / Emma Baxter
* 2007 - 2016: Médecins - Stella Illot / Amy Hays / Lizzie Clarke...
* 2016: Wolfblood Secrets - Agent Jones
ANOVA

Comparison of means of two or more populations. A way to examine group of responses that are measured on interval or ratio scales.

Dependent variable must be metric. There must be one or more independent variable that is categorical. A categorical independent variable is called a factor. If there is a combination of categorical and metric variable, the technique is called ANCOVA. One way ANOVA is usually called so because there is only one categorical variable. If the mean is compared against n categorical variables, it is called an n-way ANOVA. A particular combination of factor levels is called a treatment.

ANOVA compares a continuous response variable(dependent) against a factor variable(independent)

ANCOVA compares a continuous response variable(dependent) against levels of factor variable while controlling for a continuous covariate.

Total Variation = Variation Within(SSerror) + Variation Between(SSx)

Eta^2 = Variation Between / Total Variation. Eta^2 is strength of effect.

Testing of hypothesis using F-statistic = [SSx/(c-1)]/[SSerror/(n-c)] with c-1 and n-c being degrees of freedom. n is the number of samples. c is the number of categories.

Assumptions of ANOVA

* error terms are not correlated
* error terms are normally distributed
* the categorical of independent variables are fixed

For n-way ANOVA:

SStotal = SSx1 + SSx2 + SSx1x2 + SSerror. The eta^2 is called the overall effect or multiple eta^2. F is calculated using SSx1x2.

Interactions are shown on the graph

If parallel then there is no interaction.

If there is an interaction it can be ordinal or disordinal. Means that there is an interaction between the variables. Need to see if the effects are significant.

For disordinal, there can be crossing or non-crossing case.

Omega squared is used as an indicator of interaction.
Focus Strategies and Niche Markets

Focus strategies is about saying No

Pick a very specific thing by segmenting a market and finding a large enough segment to produce a profit.

Can try and specialise on customers, products or geographical area.

Focus Strategies

* If one competitor decides to target in one thing, you have to target another to be profitable.
* This is assuming the two competitors are providing goods/services of different quality.
* For there to be equilibrium, there needs to be a focus. No incentive for one firm to steal consumers away from their competitor.
* One firm has to have a price in one range and the other must have the price in another range
* Must stay in this range
* Must have a minimum price and maximum price.
* Willing to pay - actually pay = consumer surplus
* Charge price to completely eliminate consumer surplus
* To induce switching one firm would need to induce a higher surplus using the price

Superstar - one big hit product/service that is producing most of the value for a large number of consumers

* Vanilla movies appealing to a large demographic. Horizontal Diff.
* Vertical(Quality) differentiation occurs in both.

Long Tail - lots of little niche products producing value for small fraction of consumers

* Low search cost and low inventory cost provide most of profit/revenue
* Finding "hidden gems"
* Edgy movies appeal to a certain demographic. Love or Hate. A small cult following. Horizontal Diff.
* Vertical diff applies here too.

Long Tail VS Superstar

* High-quality producers want mass market design
* Low-quality producers want a niche market design
* Less search cost leads to niche design
* Superstar effect: More searching leads to more high quality
* Long Tail effect: More competition leads to more niche targeting
* Polarised to mass market appeal and niche appeal so there is no middle
Cost and Benefit Advantage

Cost Advantage

* More cost efficient firms drive the less cost efficient firms out
* Replacement Effect occurs when the most efficient firm becomes more efficient and takes its own place as the cheapest.
* Less competition means less incentive to become more cost efficient. Replacement effect happens rarely.
* Incremental and Disruptive cost reduction.
* Incremental does not do much.
* Disruptive changes the market drastically. The cost is much lower than all the others. Compare MC, marginal cost, of pre-innovation and post-innovation.

Benefit Advantage

* Differentiation index some random greek letter. If = 1 then homogenous. If = 0 then completely differentiated.
* Hotelling(Horizontal Differentiation)
* On street. Products more or less homogenous. The only difference is the distance the consumers have to travel.
* Need to find the indifferent customer. Equate the willingness to pay. Willingness to pay is value/utility gained from product/service minus personal cost, in this case, distance. In this case, the indifferent will be in terms of x, the consumer because profit = (p-c)x.
* Find what will satisfy the indifferent customer and apply it to profit maximisation problem to find optimal price and distance.
* Find p1,p2 and l. Differentiate the profit function(one exists for each of the two firms) in terms of p1, p2 and l.
* Demand Effect - fixed price, less differentiation leads to more demand
* Rivalry Effect - increasing differentiation softens competition
* Vertical Differentiation
* Also need to find indifferent customer. Find the **utility(the theta)** associated with quality. Surplus from quality\*taste for quality - price is the utility. Equate the two different utilities to find indifferent.
* Demand is the indifferent utility and 1 - indifferent utility each
* Question solving
	+ Find utility function of high qual and low qual
		- will have a variable for individual customer preference
	+ Equate them and find the indifferent preference, the indifferent customer. Don't care which one to buy. This is the quantity.
	+ Profit maximise. Put in the profit function the indifferent customer/preference. Diff by low qual/high qual price. This is the best response of price to another's price and qual.
	+ Do the same for the other price. Will get in terms of other firm's price and in quality.
	+ Equate them and find purely in terms of quality.
	+ Insert back into profit function the price in terms of quality. Now profit is only in terms of quality of the two rival firms.
* If rival chooses high I choose low.
Правила игры

* 1. Не использовать нецензурные слова, вести себя вежливо перед другими игроками;
* 2. Не спамить, тем самым засоряя базу. Спам - умышленное действие. Им называют

частые отправки зачастую однообразных сообщений. Спам зачастую доходит до лагов
и багов внутри игры.

* 3. Не использовать "дыры" в игре для начисления валюты и других достижений.
* 4. Не использовать посторонее ПО (Программное Обеспечение) для получения

достижений в игре и начисления валюты.

* 5. Не сообщать другим свои данные, пароли.
* 6. Не вымогать, требовать, просить за достижения в игре, подарки и бесплатно

номер телефона и данные. Правило распостраняется и на обмен внутри игры.

* 7. Не использовать для получения достижения посторонние сайты.
* 8. Не представляться Администрацией игры, Шерифом и главным Шерифом.
* 9. Не использовать ники с нецензурной лексикой, матами, оскорблениями,

или ники, затрагивающие политические конфликты и политику в целом.
Walleye

10 - 30 (4,5 - 13 kg)
**Kenai River**
Deadwater Creek
20 - 50 (9 - 22 kg)
**Kenai River**
Boundless Waters
Boundless Waters (Night)
Infinite ValleySunview Shores

## Walleye in Real Life

The walleye (Sander vitreus, synonym Stizostedion vitreum), also called the yellow pike or yellow pickerel, is a freshwater perciform fish native to most of Canada and to the Northern United States. It is a North American close relative of the European zander, also known as the pikeperch. The walleye is sometimes called the yellow walleye to distinguish it from the blue walleye, which is a color morph that was once found in the southern Ontario and Quebec regions, but is now presumed extinct. However, recent genetic analysis of a preserved (frozen) 'blue walleye' sample suggests that the blue and yellow walleye were simply phenotypes within the same species and do not merit separate taxonomic classification.

In parts of its range in English-speaking Canada, the walleye is known as a pickerel, though the fish is not related to the true pickerels, which are members of the family Esocidae.

Walleyes show a fair amount of variation across watersheds. In general, fish within a watershed are quite similar and are genetically distinct from those of nearby watersheds. The species has been artificially propagated for over a century and has been planted on top of existing populations or introduced into waters naturally devoid of the species, sometimes reducing the overall genetic distinctiveness of populations.

IRL Max Weight: 29 lbs (13 kg)

IRL Found in:

* Bow River (Yes)
* Kenai River (Yes)
Make vs Buy

Ownership of assets

If you own assets you are more likely to invest in it, outside of the contract, so that it improves better and benefits you/company.

Investment carries a personal cost which is deducted from overall calculations. As long as investment carries a net positive impact on profits then it will be done. delta pi is the increase in profit from investment and I is the personal investment cost. Pi + delta pi - investment is the surplus. If one surplus is larger than the other, then the other should own the asset (either worker or boss).

The rent is in the form of profit - utility 1 and utility 2. Each utility representing the utility a worker gets. They share this equally(\*1/2) and also get an individual utility payment of u.

The workers will invest as long as the gain from investing (delta pi + utility 1)\*1/2 is larger than the investment I.

Owning an asset gives incentives to invest in that asset but disincentivises the other party in investing in those relationship-specific assets. No bargaining so efficient contractability of investment leads to under-investment.

Incentives

Ownership of assets give control of residual rights/decision making and confers residual payoffs

You get what you pay

You give up ownership of assets to workers so that worker goals and firm goals are aligned

Surplus(to firm) = Profit + asset value - personal cost

Worker benefit = wage + bonus\*performance - personal cost

Worker has two action choices. Need to optimise for each to find optimum course of action. One action is for profit. The other action is for asset value.

But ownership of asset by worker(non-integration) gives excessive incentive for the worker to invest to increase the value of the asset. This reduces surplus.

In integration the asset value is not counted towards the worker's performance the worker will not invest personal cost into improving value of asset. As a result surplus will fall.

Ownership may be the only way to induce the investment into assets by workers. Ownership provides incentives that can't be replicated through owning the asset.

Outsourcing

* Reasons to do them: Producer has economies of scale/learning, Externalising production may lead to better measurement allowing for higher incentives, Transferring asset ownership may boost incentives.
РеРайс вики

## Добро пожаловать на **РеРайс вики**

"РеРайс - должно быть, странное название? Нет. Окончание Райс сохранилось как память о СмешРайсе,его придумал Илья Карасик, а приставка РЕ является так же приставкой слова (ре)конструкция, (пере)работка"

РеРайс - это удивительная страна, где ты в ближайшем времени сможешь почувствовать себя
поваром и приготовить настоящие блюда, создать и обустроить свой ресторан, повысить свою
репутацию, поиграть в разные игры, полностью изменить своего персонажа и стать уникальным,
а главное сделать красивый и уютный домик, и регулярно устраивать в нем вечеринки!

## РеРайс

### Группа ВКонтакте :

https://vk.com/reriseoff

* Все статьи вики
* Все участники
* Категории
* Свежие правки
* Самые Активные Участники

## Создать страницу

Вы можете улучшить эту вики. Создайте новую статью!
<createbox>
width=24
break=no
buttonlabel=Создать новую страницу
</createbox>
Так же вы можете улучшать уже созданные страницы

## Галерея

1/15
Шарарам-9

### Игра создана :

10 авг. 2014 г. (по крайней мере, первая запись в офф. группе была 11 авг. 2014 г.)

## История

Мне пришлось долго смотреть группу Шарарам-9, но всё таки я кое-что нашёл :

### Начало

"Всем привет! Добро пожаловать в Официальную группу ШАРАРАМ-9!
Да, Мы понимаем, копипасты, клоны и т.д но все же, нам не чего делать и мы решили создать вот такую вот игру.
Начинается 2 день работы (рисуем локации)
Сейчас я предоставлю Вам скрин домика (это была тест.локация, но мы решили сделать ее домиком, и у нас получилось"-первая запись с офф. группы, которая сохранилась до этого времени. Дата создания этой записи : 11 августа 2014 года. И, это тот самый (почти) домик, который вы, скорее всего, уже видели в игре :

###

### Билеты на самолёт

Того же дня (11 августа) выложили запись :

> "Перед вами таблица билетов на самолет ( у нас будет такая локация.)
>
>
> Посмотрите, какая вам подходит.
>
> Цена не указана. Скоро будет компактная таблица (ее нужно скачать)
>
> Там будет все указано
>
> (Это блокнотик)
>
>
>
>
> Смотрите.
>
>

И была эта картинка :

И, все мы знаем, что в игре СмешРайс этого не реализовали (но, кто знает, может в самоооом Шарараме-9 (игре) была такая возможность, купить билеты и полетать на самолёте).

### Хождение

> "!\_Внимание!\_Внимание\_!
>
> Разработчики нашей игры постарались сделать вам скрин с локацией и смешариком! Версия первая, ее нужно переделать в иллюстраторе. Как это будет выглядеть - можно посмотреть там. Но примерно так будет выглядеть."
>
>

Но, этого не было в СмешРайсе.

### Окошки/Спойлеры с квеста "Потоп в СмешРайсе/Шарараме-9"

Разработка квеста "Потоп в Шарараме-9" или же "Потоп в СмешРайсе" велась ещё оочень давно - с 11 сентября 2014 года.

    И, через 10 дней (21 сентября), был опубликован первый спойлер :

> "всем привет! Угадай к чему это все и напиши в комментариях! "
>
>

Позже, на следующий день (22 сентября) был опубликован ещё один спойлер :

> "Секретно!
>
>
>
> Какие окошка будут в квестах? Смотри тут!
>
>
>
>
> Ответы замазаны :3 2 вопроса еще недоработаны"
>
>

```
Продолжение следует...

```

## Закрытия Шарарама-9

1 октября 2014 года (наверное) первый раз закрылся проект "Шарарам-9"

> "ВНИМАНИЕ! ПРОЕКТ ЗАКРЫТ
>
>
>
> как только сделаем квест,а именно не точная дата, то сообщим вам(проэкт откроется ибо появится какая то активность)
>
> сайт открыт для общего доступа
>
>
>
>
> Спасибо всем тем кто поддерживал наш проект во время трудных моментов... Большое вам спасибо!"
>
>

17 октября 2014 в группе был опубликован ещё пост :

> "проект закрыт на всегда.
>
> ждите откличек, регулярно проверяйте группу"
>
>

Также, уже 25 января 2015 года проект опять был закрыт :

> "ЗАКРЫТО.
> всем спасибо! Ждите новостей,если они будут"
>
>

Позже, проект снова был открыт, уже от имени Ильи Карасика.
Le Dohldrenc

Le Dohldrenc est une potion des Wolfblood sauvages que Jana Vilkas a donnée à Shannon Kelly.

 Dans la Saison 2, l'épisode "La Reine de la Lune", il est destiné à travailler comme un inhibiteur de peur, un moyen de surmonter ses propres limites. Il est démontré pour avoir un effet fort sur les humains si on en a trop pris, leur donnant la capacité d'être capable d'entendre et sentir tout autour, alors qu'il peut causer votre pression artérielle à augmenter (comme nous voyons avec Shannon Kelly). Comme il est censé être pour les Wolfblood, Maddy Smith crie à Jana Vilkas pour lui donner la potion. Shannon est toujours obsédé par elle, car elle pense qu'elle a augmenté ses sens et elle continue à demander à Jana pour avoir la recette.