To get an accurate depiction of your menstrual cycle, start counting on the first day of your period. Make a note on your calendar or in a menstrual cycle monitoring app when your period begins. Smartphone apps such as Clue, Glow, Eve, and Period Tracker are designed to help you monitor your menstrual cycle, ovulation, and other key points in your cycle. They can be an easy and data-driven means of monitoring your cycle length. Your count resets on day 1 of your menstrual cycle. This means that your count for each cycle should end on the day before your next period. Include a count for the day before your period starts, but do not include the start date of your period, even if it starts later in the day. If, for example, your cycle started on March 30 and your next period came on April 28, your cycle would be March 30 to April 27, and would total 29 days. The length of your menstrual cycle may vary from month to month. If you want an accurate depiction of your average cycle length, monitor your cycle for at least 3 months. The longer you monitor your cycle, the more representative your average will be. Find the average for the length of your cycle using the numbers you collected while counting your period. You can recalculate this every month to get a more accurate depiction of your general cycle length. Remember, though, that the average shows a trendit doesn't definitively represent the length of your next cycle. To find the average, add the total number of days of your cycle for each month that you have monitored. Then, divide that total by the number of months you monitored. This will give you your average cycle length. For example, you had a 28 day cycle in April, a 30 day cycle in May, a 26 day cycle in June, and a 27 day cycle in July, your average would be (28+30+26+27)/4, equalling a 27.75 day average cycle. Keep tracking your cycle every month. Even if you pass a certain target, such as getting pregnant, keeping track of your cycle throughout your life can help you know when something is off. Medical professionals often ask for information about your cycle, as well. Monitoring your periods and cycle length will help you provide the most accurate information possible. If your doctor asks you the date of your last period, the answer is the first day of your last period, not the day it ended.
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One-sentence summary -- Start counting on the first day of your period. Count up to the day before you start your next period. Monitor your cycle for at least 3 months. Calculate your average cycle length. Continue to track your cycle.

frequently. Always wash up with hot water and soap after handling raw meat, poultry, or seafood. Don't just dip your hands under water for 2 seconds. Wash them vigorously for a minimum of 20 seconds. Cell phones and computer keyboards are among the germiest surfaces, so remember to wash up after checking a recipe or sending a text. Wash produce under cold running water, and don't use soap or detergent. Soak broccoli, cauliflower, and other items with lots of nooks and crannies in a bowl of cold water for 1 to 2 minutes. If you're storing washed produce, place it into a new container instead of into its original package. Switch or wash the boards and knives you used to prepare raw meats before using them to prepare produce. Don't store raw meat on a platter, then use the same platter to serve cooked meat. For instance, don't season raw chicken on a cutting board, then use the same cutting board to chop broccoli. Even if you plan on cooking the broccoli, it might not reach the internal temperature required to kill germs in raw chicken. Replace your cutting board if it has deep, hard to clean grooves. Pouring required amounts of salt, pepper, and other seasonings into small bowls might mean you'll have to do a few more dishes. However, you won't have to grab seasoning packages with unclean hands or run to the sink each time you rub the meat with an ingredient. For instance, rub your chicken breast with salt, then reach for the bowls with pepper, garlic, and paprika. Wash your hands and the bowls when you're done seasoning. Never marinate meat on the countertop or leave it unrefrigerated for extended periods. Excess marinade can make a great pan sauce, but marinade that's touched raw meat is a major health hazard. Boil it for at least 1 minute before serving it as a sauce. You can also prepare extra marinade, divide it, and keep a portion of it away from raw meat. Wipe down surfaces with a kitchen cleaner or a diluted bleach or vinegar solution. Use paper towels or a cloth designated for countertops and other surfaces. Don't use the same sponge or cloth to clean both your dishes and countertops. Don't forget about the sink, which harbors germs and residual food. Rinse away or pick up organic matter, then wipe it down with a cleaning solution.
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One-sentence summary -- Wash your hands Rinse fruits and vegetables before cutting them. Use separate cutting boards and utensils for raw and ready-to-eat foods. Place seasonings in small bowls when working with raw meat. Marinate meat in the fridge and boil extra marinade before serving it. Wash all counters and surfaces after preparing raw foods.

Numbers are what a data analyst works with every day, so you want to make sure you're comfortable with math. Having a firm understanding of college algebra is important; you should know how to do things such as interpret and graph different functions as well as work through real life word problems. Knowing multivariable calculus and linear algebra will help as well. To become a data analyst, you'll need to be able to interpret data, which is where statistics comes in. Start with a foundation of high school- or college-level statistics, and then move on to more challenging information that might be required for the job. Mean, median, and mode, as well as standard deviation, are examples of the kinds of statistics concepts you would learn in high school or college. Having a strong grasp of both descriptive and inferential statistics will be helpful as well. While you don't need to be an expert at coding or programming to start off as a data analyst, you should be comfortable doing it on a small level. Start by learning how to use programs such as Python, R, and Java first, and then work your way up to others. SQL programming is another that is common among data analysts. You can take courses online to learn coding and programming. Once you've analyzed your data, you'll need to be able to talk about it with others. Work on being able to explain complicated information in a way that makes non-data analysts understand your findings, and practice using programs that illustrate the data in a visually-helpful way. You should be able to communicate data visually as well as verbally. Understand how to use tools such as ggplot and matplotlib to illustrate your findings. You'll be organizing data and calculating numbers as a data analyst, so you need to be comfortable using Excel. There are many video tutorials online, as well as free sites, that will help teach you all you need to know about using Excel to its full potential. Teaching a computer to come up with predictions or decisions on its own after it has studied data, or machine learning, is important when dealing with data analysis. Look online to find courses you can take that will teach you all you need to know about machine learning, and some of them are even free. To understand machine learning, you'll need to have a foundation in programming and statistics. There are three types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. An example of supervised learning is your email filtering your inbox and putting spam in its own folder. Supervised learning would be when Netflix suggests television shows or movies that you might like, and an example of reinforcement learning is a self-driving car and its ability to see and then adapt to its surroundings.
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One-sentence summary --
Master college-level algebra. Understand statistics. Work on your coding and programming abilities to be a more appealing candidate. Develop strong communication and presentation skills. Familiarize yourself with Microsoft Excel. Learn about machine learning.