Difference between revisions of "Links: Stat 202 Summer 2016"

Revision as of 04:17, 2 August 2016

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

• Exam 1 Practice 1 (solutions).

• Exam 1 Practice 2 (solutions).

• Exam 1 Practice 3 (solutions).

• Exam 2 Practice 1 (solutions).

• Exam 2 Practice 2 (solutions).

• Exam 2 Practice 3 (solutions).

• Midterm Exam (solutions)

• Exam 3 Practice 1 (solutions)

• Exam 3 Practice 2 (solutions)

StatCrunch Skills We Covered (copied from Summer 2015, but still relevant)

StatCrunch Plots

• Bar Graph
• Pie Chart
• Stemplot
• Histogram
• QQ-Plot (Normal Quantile Plot)
• Scatter Plot
• Scatter Plot with Regression Line overlaid
• Residual Plot
• Boxplot

StatCrunch Calculators

• Normal Calculator
• Binomial Calculator

StatCrunch Statistics

• Summary Stats (Columns)
• Summary Stats (Correlation)
• Regression (Simple Linear)

Other StatCrunch Skills

• 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

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

Confidence Interval Width/Sample Size

• Z-Stats
• T-Stats
• Proportion Stats
• One Sample
• Two Sample

Some Other Things to Review for Final

• Know how to use the 68-95-99.7 Rule.
• Be able to recognize when to use each type of test of significance listed above, and each type of confidence interval listed above.
• Know how to interpret the results of tests of significance and confidence intervals.
• Know what a p-value is. Know the definition and remember it!
• Know what a null hypothesis is, and what an alternative hypothesis is, and the difference between the two (they are not interchangeable!)
• Know that a small p-value, i.e. less than alpha, means the result is significant, which means you reject the null hypothesis, in favor of the alternative hypothesis: you have compelling evidence that an effect is there, a positive result. Traditionally alpha = 0.05.
• Know that a large p-value, i.e. greater than alpha, means the result is insignificant, which means you fail to reject the null hypothesis: you do not have no compelling evidence that an effect is there, a negative result. Again, traditionally alpha = 0.05.
• Know the difference between a one-sided alternative hypothesis and a two-sided alternative hypothesis. Know that unless you are sure that you should use a one-sided hypothesis, that you should always use a two sided hypothesis. Know that two-sided hypotheses is more conservative--significant results with a two sided hypothesis are significant with a one-sided hypothesis in the appropriate direction.
• Don't make the following mistake, WRONG: "a p-value greater than alpha means the result is significant:" THIS IS WRONG! In the past, students with this confusion made the same mistake on several problems and lost a lot of points on each, a costly mistake, but it reveals that you don't really understand tests of significance, which justifies a low grade. BE WARNED AND BE CAREFUL! You won't make this mistake if you know what a p-value is and why it needs to be small to reject the null hypothesis and find an effect. Make a habit of checking your understanding with your conclusion, each time you draw a conclusion.
• Know how to use the Binomial calculator, when to use it, and how to recognize when a problem requires it.
• Know how to use the Normal calculator, when to use it, and how to recognize when a problem requires it.
• Know about sampling distributions for mean, counts and proportion. Know what is the mean of the sample means, the mean of the sample proportions, and the means of the counts. Also know about the standard deviations of these things, and when these distributions are approximately Normal. I will give you the formulas on a formula sheet in the beginning of the exam BUT know how to use them and know how to recognize when they need to be used.
• Calculate the mean of a random variable.