Shiny practice items 'Statistics and business analytics', module 4

This app allows you to practice various aspects covered in this module.

Please make sure that you have fully completed the following tasks before continuing with this app:

1. Read the module's learning plan

2. Watch the topic videos and review the lecture notes

3. Work through the SPSS How to guide



The module has the following objectives:

1. Describe the difference between univariate statistics and bivariate statistics

2. Use a t-test to compare two means

3. Perform an ANOVA to compare more than two means

4. Carry out bivariate statistical analyses using SPSS



Please proceed with the practice items by clicking on the links in the top bar of this app. It is not necessary to complete these items in order. We encourage you to work together with a classmate!

There are three types of practice items: theory ('TH'), SPSS ('SP') and multiple choice ('MC').

These practice items will help you come prepared to the lab and help you perform better on the quizzes.

Thus, you should complete these practice items before joining the lab meeting corresponding to this module.

MBA program
Peter Ebbes


Topic

Univariate and bivariate statistics


Lecture

topic 1, Uni- versus bi-variate statistics


Purpose

Practice identifying how many variables and their scale level. Let's do it!


Question

An important first step is to identify given an managerial question or problem how many variables (or columns in your data table) are needed to address the question, and what the scale level(s) is (are) of the variable(s).

For each of the following cases, identify how many variables are involved and what the scale levels are of the variables. You may have to also brainstorm a bit of what data you would need to collect to address the question.


Case 1

The data science team at LinkedIn is asked to identify, relatively speaking, how many of their users are having a post-college degree compared to a high school degree only.



Case 2

The MBA office asks you to investigate which section (ES1, ES2, etc.) was more satisfied with Data Science Camp, or whether there were no differences.



Case 3

The president is wondering whether men or women are more likely to vote for the green party.



Case 4

Linda is selling ice creams on the beach. She is wondering whether the sales of icecream are affected by temperature.



Topic

ANOVA and mean comparisons


Lecture

topic 3, Comparing more than two means


Purpose

Practice interpreting the results of an ANOVA test. Let's do it!



Question

What do you conclude from these analyses?




Topic

Bivariate statistics -- t/Z test


Lecture

topic 2, Comparing two means


Purpose

Practice carrying out the 6 steps of hypothesis testing for two means by hand. Let's do it!





Topic

Practice working with SPSS


Lecture

topic 2, Comparing two means

topic 3, Comparing more than two means

This activity is only useful if you have reviewed the corresponding SPSS How to guide.


Purpose

Use SPSS to test hypotheses about the population. Follow the following managerial/research questions to further practice your SPSS skills. Let's do it!


In this module you learned about comparing means when your analysis requires you to use a quantitative variable and a categorical variable at the same time. SPSS can easily perform such analyses for you. It is always a good idea to write down the 6 steps of hypothesis testing on scratch paper, even when using SPSS. Practice conducting a t-test and an ANOVA with SPSS following two scenarios from the American Express mini mini-case (module 1, SPSS file 'mini_case_AE_credit_card_web.sav').


Question 1

Suppose you are interested in monthly credit card spending in the grocery category. You are only interested in how much customers spend once they have made the decision to use their primary card for groceries. Such an analysis can be interesting for instance if we believe that the first decision is whether or not to use the primary card to pay, followed by the second decision of how much to spend. Here we would focus on the second step. In other words, in your analyses, you should ignore the zeros (a zero means that presumably the customer did not use their primary card that month to buy groceries). In particular, you are interested in comparing the spendings (on average) of men and women, irrespective of their card brand. What do you conclude? Are the monthly grocery spendings using the primary card, on average, higher for men or women? Or is there no difference?



Question 2

Following the previous question, suppose that you want to know whether there is a difference, on average, between the primary card brands with respect to monthly grocery spending (again, conditional on users having decided to use the card). How would you proceed? What analyses technique should you use? What is your conclusion?



Topic

Five multiple choice practice questions


Lecture

Module 4, all topics


Purpose

Test your knowledge about the subjects of this module. Let's do it!


1. Which of the following expressions about bivariate statistics is not true? Select e. if you think that all statements are true.


2. Which of the following is not needed for ANOVAs? Select e. if you think that all are needed for ANOVAs.


3. Which of the following tests would you recommend to test $H_{0}: \mu_{1}=\mu_{2}=\mu_{3}$?


4. Joe is comparing two means in his research study. He is trying to explain to his colleague who does not know much about statistics what the deal is with the Z (or t)- test statistic. Which of the following expressions about this test statistic is true?


5. A researcher at a pharmaceutical company tests a new drug on mice. The researcher tests two variations of the drug and uses also a placebo control group. The researcher measures the temperature of the mice in celcius. The hypothesis is that the drug should lower the body temperature of the mice. Mice are randomly assigned to either drug A, drug B or the placebo drug. Which of the following expressions regarding this scenario is true?