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Mail S. Kellogg

Given a sample mean and true standard deviation, be able to calculate a confidence interval for the true mean.

Given a sample mean and sample standard deviation, be able to calculate a confidence interval for the true mean.

Given a sample variance be able to compute a confidence interval for the true variance.

Be able to compute a sample size needed for a given precision level for a true mean; standard deviation known.

Be able to outline how to calculate a sample size for given precision level for a true mean; standard deviation unknown.

Know the underlying assumptions when using the sampling distributions.

Given a word statement, be able to state the null hypothesis, the alternative hypothesis, and the appropriate test statistic.

Be able to conduct a two tail hypothesis test for

- True mean given a sample mean; standard deviation known.

True mean given a sample mean; standard deviation unknown.

Difference between two means; standard deviations known.

Difference between two means; standard deviations unknown.

Difference given paired data; standard deviation unknown.

True variance given a sample variance.

Ration of variance from two populations given two sample variances.

Know the underlying assumptions when using the sampling distrutions for hypothesis testing.

Given a data set and summary statistics be able to calculate

- Sum of squares of x about x.

Sum of squares of y about y.

sum of squares of y about x.

sum of residuals squared.

esimtated parameters a and b.

T-statistic for a.

T-statistic for b.

- Given a regression output, be able to

Conduct a test of significance for a or b.

Calculate a 95% confidence interval of y-hat.

Given a data set and associated scatter plot, be able to identify an appropriate transformation.

Given a data set, scatter plot, and two or more outputs, be able to select the best transformative model.

Given a data set, transformation, and an output. Be able to predict the response y for a given value of x.

Polynomial Regression

Given a data set and associated scatter plot, be able to identify an appropriate polynomial model.

Given a data set, polynomial model, and an output, be able to predict the response y for a given value of x.

Multiple Regression

Given a data set and associated output, be able to determine which if any variables should be excluded from the model.

Given a data set, associated output, and residual plots, be able to do a residual analysis.

Given a data set and associated output, be able to predict the response y for a given

Given a data set and associated outputs, be able to determine which which subset of variables is appropriate for inclusion.