Module 1 DQ 1
The media often attempts to predict the outcome of national elections. Why are they often wrong? Based on the concepts presented in this module’s readings, how could the system be improved?
Module 1 DQ 2
In conducting a survey, what do you think is even more important than the size of the sample? Why?
BUS-352 | Analysis Using Graphs and Descriptive Statistics
Module 2 DQ 1
Referring to Chapter 2 Excel Guide, EG2, Section EG2.5 in the textbook, create a histogram on some sample data using Microsoft Excel. Post your file to the Discussion Forum in response to this DQ. What are some specific challenges related to creating a histogram in Microsoft Excel?
Module 2 DQ 2
What ethical issues should you consider when creating a graph of data?
BUS-352 | Probability
Module 3 DQ 1
Assume the financing gurus of a weekend investment television program predicted a 50% chance of XYZ stock gaining in January and a 50% chance of gaining in February. Your financial advisor sees this and tells you there is a 100% chance XYZ stock will gain over the 2-month period. Would you continue to use this financial advisor? Explain.
Module 3 DQ 2
Marie claims she can predict the sex of pregnant women’s babies. She sees 1,000 women a year, and she always predicts a female. She charges $1,000 for a prediction, and she always predicts a female (although clients do not know that). When she is wrong, she offers a double-your-money back guarantee. Since the chance of having a female is approximately 50%, how can she earn any money?
BUS-352 | Discrete and Continuous Probability Distributions
Module 4 DQ 1
Provide some examples of discrete and continuous variables. What attributes of these variables make them discrete and continuous? Why?
Module 4 DQ 2
Describe the term mutually exclusive. Provide some examples. Must the values of x in a discrete probability distribution always be mutually exclusive? Why or why not? Provide an example.
BUS-352 | Sampling Distribution and Confidence Intervals
Module 5 DQ 1
You just saw an ad on television that states the majority of the population would vote to make smoking illegal. The poll that is referenced shows 53% of those asked supported making smoking illegal. In the fine print at the bottom of the screen, you see that the margin of error is +/- 3%. What is your reaction? Explain.
Module 5 DQ 2
Many people believe that a larger sample is always better. What do you think? Explain.
BUS-352 | Hypothesis Testing With Single Samples
Module 6 DQ 1
Your mayor just announced that the local unemployment rate dropped last month from the prior month. It went from 10.5% to 10.4%. Is this a significant drop? Explain.
Module 6 DQ 2
Give an example of a situation in which you believe a Type I Error is more serious. Give an example of a situation in which you believe a Type II Error is more serious. In each case, why do you think so?
BUS-352 | Hypothesis Testing With Two Samples
Module 7 DQ 1
Describe when a z-test should be performed as opposed to a t-test? Which (if any) can we use all the time? Why or why not?
Module 7 DQ 2
Your manager, who just read an abridged version of a statistics book, wants you to test hypotheses for the difference in two population means. The sample sizes for each are 23. He is adamant that you perform a z-test. What would you tell him? What specific explanation would you give?
BUS-352 | Additional Topics
Module 8 DQ 1
A market researcher is interested in knowing the type of training that works best for DVD users. Thirty consumers are randomly selected from a population of known DVD owners (i.e., users). Ten users are trained by giving them the DVD user’s manual and allowing them to read it. Another 10 users are trained from a 30 minute DVD user training video. Another 10 users are trained from a self-paced computer tutorial. The users are then timed in their ability to setup and program the DVD by performing a series of operations. Which statistical analysis technique should be used? What is the null hypothesis? Can the market researcher get an answer? Why or why not?
Module 8 DQ 2
A client gives you a data set of 30 observed values that represent the number of gallons of gas that 30 individual Nissan Sentra owners purchased at the gas pump last month. Your client wants to know if the data set represents a normal distribution. Which statistical analysis technique should be used? What is the null hypothesis? Can an analysis be performed? Why or why not?