Links: Stat 202 Summer 2016
From Sean_Carver
Contents
Links
- Online textbook: http://www.macmillanhighered.com/Catalog/Product.aspx?isbn=1464133409
- Kahn Academy videos on why you divide by (n-1) instead of (n) when you compute the sample standard deviation or sample variance. Video 1: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/v/review-and-intuition-why-we-divide-by-n-1-for-the-unbiased-sample-variance Video 2: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/v/simulation-showing-bias-in-sample-variance
- How to interpret a Normal Quantile Plot (QQ-Plot): http://stats.stackexchange.com/questions/101274/how-to-interpret-a-qq-plot
- Comparison of Normal and T Distributions
Practice Exams And Exams
StatCrunch Skills Taught During Summer 2015, Before Midterm
StatCrunch Plots We Have Taught Before Summer 2015 Midterm
- Bar Graph
- Pie Chart
- Stemplot
- Histogram
- QQ-Plot (Normal Quantile Plot)
- Scatter Plot
- Scatter Plot with Regression Line overlaid
- Residual Plot
- Boxplot
StatCrunch Calculators Taught Before Summer 2015 Midterm
- Normal Calculator
- Binomial Calculator
StatCrunch Statistics Taught Before Summer 2015 Midterm
- Summary Stats (Columns)
- Summary Stats (Correlation)
- Regression (Simple Linear)
Other Skills Taught Before Summer 2015 Midterm
- Load Data
- Delete and Insert Rows And Columns
- Rename Columns
- Simulate Data From A Specified Distribution
- Use Fixed and Dynamic Seeds
- Apply Transformations to Data
StatCrunch Skills Taught During Summer 2015, After Midterm
Sampling
- Conduct a random sample of data
- Sample if there is more than one column and you want sampled columns to correspond.
- Use fixed seeds for sampling
- Generate a sequence of numbers to use for sampling.
Hypothesis Testing
- Z-Test
- T-Test
- Proportion Test
- One Sample
- Two Sample
- Paired
- With Data
- With Summary
Confidence Intervals
- Z-Stats
- T-Stats
- Proportion Stats
- One Sample
- Two Sample
- Paired
- With Data
- With Summary
Power/Sample Size
- Z-Stats
- T-Stats
- Proportion Stats
- One Sample
- Two Sample
