Not too easy. Not too difficult.
Recommended for anyone looking for a semi-challenging math class different from the traditional math classes like Pre-Calc and Calculus. Instead, this course has less math and more reasoning and written responses, using data to prove claims.
Topics covered 1st semester: describing one variable data in center, shape and spread, analyzing boxplots, histograms, scatterplots and bar graphs in both one variable and two variable distribution, correlation and regression lines between distributions of data, surveys and experiments, probability and the normal model. 2nd semester: normal models, estimation and confidence intervals in categorical and quantitative data, hypothesis tests with categorical and quantitiative data in one and two data sets, chi squared test
Hours per week:
Advice for students:
Paying attention in class, doing all homework, participating in classroom discussion is essential in solidifying all the material for this class. Understand when to use mean vs median, IQR vs standard deviation etc for comparing data distributions, be able to write complete sentences describing the distributions. Second semester is harder, especially understanding the concepts of sampling distributions and statistics vs population. Make sure to understand all the confidence interval and hypothesis test differences as there is variation between all the different types. Again, be able to write complete sentences for the confidence intervals and hypothesis tests.