In this course, you will explore basic principles behind using data for estimation and for assessing theories. You will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. You will learn how to construct confidence intervals. You will also use sample data to assess whether or not a theory about the value of a parameter is consistent with the data. A major focus will be on interpreting inferential results appropriately.

WHAT YOU WILL LEARN

• Determine assumptions needed to calculate confidence intervals for their respective population parameters.
• Create confidence intervals in Python and interpret the results.
• Review how inferential procedures are applied and interpreted step by step when analyzing real data.
• Run hypothesis tests in Python and interpret the results.

SKILLS YOU WILL GAIN

• Confidence Interval
• Python Programming
• Statistical Inference
• Statistical Hypothesis Testing