Management : Statistical Inference in Management Spring 2015 - Dr. Delaney.
1. You belong to a student group who is trying to raise money for a local charity that you feel passionately about. The top priority of this group is to raise as much money as possible selling peanuts at the university football games. You want to know whether class standing (i.e.
freshman, sophomore, junior, or senior) will make a difference in the number of peanuts sold.
You are looking to see if "class standing" affects the "level of sales". So, for each student selling peanuts you measure how many peanuts they sold, then you found an average for each group of students. Your graph looks like this:
Identify the following variables:
• Independent variable (IV):
• Number of levels of IV:
• Quasi or True experiment:
• Dependent variable:
• Between or within participant design:
• In this study, what is the operational definition of "class standing"?
• In this study, what is the operational definition of "level of sales"?
2. You work for a small company that has recently designed a new program to treat obesity. There is the potential to make large profits, but first you need to test to see if it works. You enroll 100 people who weigh more than 50 pounds more than their ideal weight. You randomly assign half of the people to participate in the program and half to diet however they choose. You are looking to see whether "type of program" (regular diet versus your program) has an effect on "body transformation" (number of pounds lost). When you are finished the data look like this: Please identify the following variables:
• Independent variable (IV):
• Number of levels of IV:
• Quasi or True experiment:
• Dependent variable:
• Between or within participant design:
• What is the operational definition of "type of program"?
• What is the operational definition of "body transformation"?
3. You've been hired by a limousine service in Pasadena, California to figure out the most efficient routes for their most highly travelled destinations in and around Los Angeles. The company employs 30 drivers who frequently drive from Pasadena to the Los Angeles Airport
(LAX). The drivers agree that there are three reasonable routes, but disagree on which is the fastest. You are looking to see which driving choice is most efficient. So, you ask each driver to drive each of the three routes and time themselves on how long it takes. You find an
average travel time for each route (averaging across the 3 drivers' times). When they are finished the data look like this: Please identify the:
• Independent variable (IV):
• Number of levels of IV:
• Dependent variable:
• Between or within participant design:
• What is the operational definition of "driving efficiency"?
• What is the operational definition of "driving choice"?
4. Complete the diagram (right) on the right with 5 "shots" on each target.
5. For each construct please think carefully about your operational definition and then determine whether it is
a) qualitative or quantitative
b) discrete or continuous
c) nominal, ordinal, interval, or ratio (level of measurement)
6. Maggie wanted to compare the median salary of male and female lawyers. Using census data she found that the median salary for male lawyers was $66,000 while the median yearly salary for female lawyers was $61,000. Please identify the following information:
• Independent variable (IV):
• Number of levels of IV:
• Quasi or True experiment:
• Dependent variable:
• Between or within participant design:
• Level of measurement for "Gender":
• Level of measurement for "Salary":
• A simple bar graph for these data might look like this:
For these data please draw a bar graph of the two means using Excel. Here are some helpful tips:
7. Stephanie wanted to compare the average temperature of three cities: New York, Phoenix, and Seattle. She found the following average temperatures: New York was 54.4 degrees, Phoenix was 72.6 degrees, and Seattle was 52.3 degrees (Fahrenheit). Please identify the
following information:
• Independent variable (IV):
• Number of levels of IV:
• Quasi or True experiment:
• Dependent variable:
• Between or within participant design:
• Level of measurement for "City":
• Level of measurement for "Temperature":
• Please use MS Excel to create a simple bar graph (as in problem above). It should look like this:
8. Propose your own "quasi" experiment, and identify each of the following:
Remember, in order for this study to be a "quasi" experiment it must NOT include random assignment of participants to the different levels of the independent variable. Common quasi-experiments might compare "subject variables" like gender or type of political affiliation or major in school.
• Independent variable (IV):
• Number of levels of IV: _________ (how many means?)
• What is the operational definition of your IV?
• Dependent variable (DV):
• What is the operational definition of your DV?
• Please complete this bar graph with the expected results
Attachment:- Management 276- Statistical Inference in Management Spring 2015 - Dr. Delaney.rar