Math 113: Study Guide Chapters 9-10

  1. Three scatter plots are given. Draw the line of best fit through each graph.
  2. Six situations are given. Provide the test (correlation, goodness of fit, contingency table) that should be used in each situation. Example: "A random sample of students is taken to see if their height is related to their sex" would be a χ2 goodness of fit test.
  3. Multiple Regression:
    1. You are the number of variables, R2 and adjusted-R2 for four different models; rank the models from best to worst.
    2. You are given four independent variables and their correlation coefficients; rank them from most correlated to least correlated.
    3. You are given the coefficients table from multiple regression; decide which three variables you would keep or get rid of.
    4. The ANOVA table from multiple regression is given to you. Work a hypothesis test, find the sample size and number of independent variables.
    5. Look at a Kolmogorov-Smirnov p-value and determine if the residuals are normally distributed.
  4. Know the properties / assumptions of multiple regression.
    1. When does the largest value of R-square occur?
    2. When does the largest value of the adjusted R-square occur?
    3. How is the Analysis of Variance used to test the regression equation?
    4. How does correlation between independent variables affect the choice of variables?
    5. What tools can be used to perform multiple regression.
    6. What are the degrees of freedom?
  5. Contingency Table:
    1. Know the null hypothesis.
    2. Find the expected frequency for one of the cells.
    3. Know the degrees of freedom and look up the critical value.
    4. Perform a hypothesis test and give a conclusion.
  6. Work a hypothesis test involving a contingency table. Know how the test statistic is affected if the order of the rows or columns is changed, the rows and columns are interchanged, and the observed frequencies are multiplied by a constant.
  7. Know the assumptions / properties of the contingency tables.
    1. What is the null hypothesis?
    2. How are the sample data selected?
    3. What requirement must be met?
    4. What type of data is used?
    5. What type of distribution does it have?
    6. How many degrees of freedom does it have?
    7. What type of test is it?
  8. Multinomial Experiment:
    1. Work a hypothesis test involving a multinomial experiment.
    2. Give the value of the test statistic when the order of the categories is rearranged or the observed frequencies are multiplied by a constant.
    3. Work another hypothesis test involving a multinomial experiment.
  9. Know the assumptions / properties of multinomial experiments.
    1. What is the null hypothesis?
    2. What requirement must be met?
    3. What is the sample data?
    4. What distribution does it have?
    5. How many degrees of freedom does it have?
    6. What type of test is it?
  10. Write a concise definition of a multinomial experiment.
  11. Regression:
    1. Look at a scatter plot and say if there appears to be any linear correlation.
    2. Work a hypothesis test involving regression.
    3. Estimate the value of the dependent variable for a specific value of the independent variable.
    4. Give the value of the test statistic when the data is manipulated or the variables are switched.
    5. Find the coefficient of determination and the amount of explained and unexplained variation.
  12. Know the assumptions / properties of Pearson's Linear Correlation Coefficient.
    1. What values is it between?
    2. What does a value of zero mean / not mean?
    3. What happens if you change the scale of either variable?
    4. What happens if you switch the variables?
    5. What type of relationship does it measure?
    6. What type of distribution does it have?
    7. How many degrees of freedom does it have?
    8. What type of distribution do the ordered pairs (x,y) have?
  13. Know the guidelines for using the regression equation.
    1. Know the guidelines for using a regression equation from page 530.
    2. What is the equation that should be used if there is no significant linear correlation (pg 528-529)?
  14. A statistical test that you have never seen before is given to you with type of test, test statistic, and p-value. Work the hypothesis test to come up with a decision and conclusion.

Notes

# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Total
Pts 3 6 14 5 7 8 5 14 5 2 15 5 5 6 100