Textual Analysis: Naked Statistics By Charles Wheelan

This semester we have learned a lot on how statistics is involved in our everyday life. We also have learned why statistic is useful in comparing things. In our book Naked Statistics by Charles Wheelan we read some chapters in where we use stats in three different ways to get close to the answer without using all the data. We see how indepednt variables and dependent variables relate to each other and how we can get close to seeing how close they relate without using the full data. Correlation is a form of statistics in where it shows us how two things are related to each other. In our book they use the example of how Netflix uses correlation to recommend shows or movies that fit your liking. In this case correlation was used to see based …show more content…
So it takes all the movies or shows you liked and is able to give you recommendations just based on that. Correlation can also determine how things effect one another. Such as temperature rising can increase the amount of people outside their house. The weather gets cold more people stay inside. Correlation can be seen in a negative way, positive way, or just normal. Correlation can be seen negatively if one of the things you are studying is related to something in a negative way. Such as the faster a car goes the destination decreases. The positive affect of the speed causes a negative affect on the distance. If a correlation is positive then it would be if you run for a long time then you will burn more calories. They both have a positive affect on each other. Correlation can be seen on a scatter plot based on how close the dots are togeather and which way they go. In a negative correlation the dots will be close togeather and be pointing downward. In a positive correlation the …show more content…
Using this type of statistic helps us understand how something can be dependent based on another variable. With this statistics we can find out how things affect one another In the real world. In this chapeter they give us an example on how low ranking jobs can affect higher rates in health issues. So we might conclude that maybe having a low ranking job will cause someone to do drugs or steal. Regression analysis helps us get closer to the dependent variable based on the independent variable. Having a low level job can affect a lot of things and regression analysis helps us remove some of those effects and can get us closer to a possible effect of low level jobs give. This analysis helps us also define what dependent variables are not a factor of the independent. Such as the book talked about how excersizing doesn’t affect cardiovascular desiese. IT helps us have an idea on what is affected in the independent variable. This helps us reject the null hypothesis that cardiocascular desease did come from excersize and we saw tht it had no relationship to it. Doing this analysis helps us understand if we should accept the null or reject it based on how it much it relates to the variable. Regression analysis can give us a linear equation which can give us the best line to how the dependent and independent relate. It is the best way to see how related they are. This is