Assignments & zyBook reading is due electonically by midnight on Monday unless otherwise noted. But, you should keep up with the reading assigned each class day (Tuesday and Thursday). Assignments are typically started in class on Tuesday or Thursday, but require work outside of class time.
Syllabus, course overview, what is data, data analytics, types of data, quantitative vs. categorical, nominal vs. ordinal, discrete vs. continuous, data visualizations
Intro to Python lanaguage, basic data types, sets, lists and tuples, dictonaries, int, float, string, importing modules, numpy, matplotlib, plotting
Pandas data frames, subsetting data, loc and iloc methods, pivot, melt, bar charts: grouped and stacked
Add/Drop Deadline
Good use of pie charts, using scatter plots to show dependent vs independent variables, regression plots, strip & swarm plots, linear trend lines, when to use line charts instead of bar charts
Quiz 1 (1.1-1.3) online
Descriptive stats vs. inferential stats, surveys, population, sampling, definition of a statistic, bias, types of sampling, arithmetic mean vs. median, outliers.
Standard deviation and variance, mean absolute deviation, visualizing min, max & range using boxplots, percentiles & quartiles.
The probability mass function and the cumulative distribution function of a probability distribution
Mean value, variance and standard deviation of a discrete & continuous random variables.
Probability density function & cumulative distribution function of a continuous random variable.
Quiz 2 (3.1-3.5) online
The empirical rule, z-score, Central Limit Theorem
Midterm Grades Due
Drop Deadline "W" Nov 1
Final Exam 8:30-10:30 RB330