Statistics is math, Statistics requires a lot of data, Data are dependable, Statistics provides unique solutions, Statistics provides unambiguous results, It is easy to lie with statistics
Cause vs Effect, Statistical Significance vs Practical Important, No Effect vs No Statistical Significant Effect, Sources of Bias, Are coincidences really improbable?, Confusion of the inverse, Averages and Variability
Confidence Intervals, Normal Distribution, Standard Deviation, Substantive Significance vs Statistical Significance and Significance Testing, Dependent and Independent Variables, Null Hypothesis, Type I and Type II Error, Power
...about data analysis
Video Interviews with Consultants from Grad Coach:
Descriptive Statistics Tips (~30 min)
Explore data, data types, visualize, distribution shapes, outliers, data presentation
Inferential Statistics Tips (~22 min)
Clear hypotheses, explore data, check assumptions, null results, what are p-values, and what they are not
| University Libraries