SPSS projects (16 problems)

Managers at all levels of an organization need adequate information to perform their respective task. One study investigated the effect the source has on the dissemination of information. In this particular study the sources of information were superior, peer and subordinate. In each case, a measure of dissemination was obtained, with higher values indicating greater dissemination of information. Using and the following data, test whether the source of information significantly affects dissemination. What is your conclusion, and what does it suggest about the use and dissemination of information?

Choose any one of the following four statistical techniques. For your selected technique, create an original final exam problem, including any required data, which could be used to test BUS678 students' knowledge. Be sure that the problem you create is truly original - do not copy a problem from a textbook or other source. Solve the problem using SPSS and send select portions of your SPSS output.

c. Correlation

A study investigated the perception of corporate ethical values among individuals specializing in marketing. Using and the following data (higher scores indicate higher ethical values), test for significant differences in perception among the three groups of specialists.

Assume you have collected data on actual incomes from people using a random sampling method. You collect the following 25 observations.
a. Is the data normally distributed - or even close?
c. Using the S.E. Mean, generate a 95% CI around the mean. What does this range tell you?

Raw data
28.00, 11.00, 10.00, 72.00, 36.00, 29.00, 25.00, 56.00, 17.00, 33.00, 23.00, 18.00, 19.00, 22.00, 8.00, 72.00, 25.00, 32.00, 31.00, 26.00, 28.00, 43.00, 18.00, 12.00, 19.00

A Factorial Design and MANOVA

This case study is divided into two separate parts. The first part requires the use of a factorial design to determine if coffee drinkers are more alert towards the end of the working day than non-coffee drinkers. The case also examines the extent to which obesity may be a factor. The second part requires that you present a set of data in an appropriate manner that allows for interpretation of the data based on an ANOVA with a Covariate and a MANOVA

Case assignment due by the end of this Module.

PART I

A Factorial Design

A) You wish to determine if coffee drinkers perform better near the end of the working day than non-coffee drinkers. You also want to know if obesity is also a factor in their ability to negotiate the maze. You develop a simple maze for the study's subjects to negotiate in timed trials. The maze requires that the subjects complete a simple task at various points before being allowed to continue. The maze and required tasks are designed to test performance abilities and one's physical abilities should not effect performance.

Before you begin this part of the Case Assignment please review the Table below. Construct a SPSS database for the study. Remember that each person participating this study falls into only one of four combinations for only TWO factors (Obese or Not Obese and Coffee drinker or Non-Coffee drinker). Therefore, there are four different conditions being measured and evaluated which are a combination of only two factors. (Hint: There are only three variables for this study (Time to complete the maze, coffee and obesity. Time is the dependent variable. Coffee and obesity are factors and are grouped variables. They are also called a coding variable in SPSS. Under "Value" click on grey box and open "Define Labels" window. Code the grouping factor of coffee as 1 = Coffee Drinker and 2 = Non-Coffee Drinker. Click on the "Add" button then repeat for Obesity. Go to: http://web.umr.edu/~psyworld/between_subjects.htm for an explanation in factorial designs. Remember, this case requires only a 2 x 2 factorial and not the 2 x 3 factorial discussed on the above linked site. Also, it may help to simplify your data before running the analysis. Once the database is set up please complete the tasks listed after the data table below:

B) Data Table for the 2x2 Factorial Design Data. Data presented in number of seconds over 2 minutes for subjects to complete the maze and tasks.

Time for Groups of Employees to Complete Maze

1. Write a Hypothesis for the subject study.

A researcher believes that she has designed a keyboard that is more comfortable to use than a standard keyboard. In order to help decide if this is the case, typing speeds were taken for 8 different people on each keyboard. The lengths of time, in minutes, for each of the people to type a pre-selected manuscript are listed below. Assume the two populations are normal. Use the data to determine if there is a significant difference in time for the two keyboards. Use .05 significance level.

Person Original New

The ages in years that 7 girls and 7 boys learned to ride a bicycle are listed below. Is there sufficient evidence to conclude that the mean ages for the two sexes differ?

Girls Boys

Assume that you have collected data on student scores on a standardized test. These students were randomly assigned to on one of two classes. Different teaching methods were used in the two classrooms. You wonder if there is a significant difference between the two classes. There are two statistical methods covered in class that could be used to solve this problem – what are they? Choose one of the two methods, state the hypotheses (H0 and H1), show SPSS results and explain which hypothesis to support (and why).

For the attached SPSS crosstab output (1stPage), discuss the association between the two variables based on the crosstab itself and on the appropriate summary measures of association.

A librarian has collected the following data, where x = carts of books to shelve and y = the time it takes to shelve them.

x y

a. Construct a scatter diagram

b. Estimate the linear regression equation E(y) = [alpha] +[beta]x

c. How much of the variation in y is explained by its linear relationship with x?

d. Test H0: [beta] = 0 against Ha: [beta] does not = 0. Report the value of the test statistic, the df, the P-value, and interpret the results.

e. Construct a 95% confidence interval for [beta] and interpret.

We are interested in studying the systolic blood pressure Y in relation to weight X1 and age X2 in a class of males approximately the same height. Data from 13 randomly selected subjects are given below.

Subject Weight X1 Age X1 Blood Pressure Y

a. Fit a multiple regression model to this data and report the prediction equation.

b. Find the predicted systolic blood pressure for the first subject. Find the residual and interpret.

c. Report R-squared and the multiple correlation and interpret.

For the attached SPSS regression output (2ndPage), discuss the association between the two variables based on the scatterplot and on the appropriate summary measures of association.

Assume that you are a wedding coordinator. Over the years you have collected data on the number of RSVP received prior to a wedding and the actual attendance at the event The coordinator believes that she can predict how many folks will attend by looking at how many RSVPed. Use SPSS to determine if there is such a relationship and show your output. If there is a relationship, how strong is it? Can you provide the coordinator with a formula that he can use to make predictions? Assume that at an upcoming event 150 RSVP. How many do you predict will attend? (3%)

We are interested in studying the systolic blood pressure Y in relation to weight X1 and age X2 in a class of males approximately the same height. Data from 13 randomly selected subjects are given below.

Subject Weight X1 Age X1 Blood Pressure Y

a. Fit a multiple regression model to this data and report the prediction equation.

b. Find the predicted systolic blood pressure for the first subject. Find the residual and interpret.

c. Report R-squared and the multiple correlation and interpret.

The Philadelphia Eagles would like to know what motivates fans to attend the games. Coach Andy Reid has gathered data on attendance, Eagles and Opponents win/loss percentage, number of games played, temperature, and whether or not his troublesome wide receiver Terrell Owens has committed some atrocity (example, called QB Donovan McNabb an idiot or some asinine public display) in the week before the game (1 = yes, 0 = no).

a) Does the Eagles win/loss percentage count?

b) Does TO’s behavior count? If so how much? Should the team dump him for attendance causes?

c) Is multi-co linearity a problem in this analysis?

d) What would be the 95% confidence interval for an attendance prediction be when the Eagles had won 75% of their games, their opponents had won 50%, they had played 8 games, the temperature was 49 degrees and TO had said earlier in the week that both Reed and Donovan should be sent to Iraq.

John Herr is an analyst for the Best Foods grocery chain. The firm operates four grocery stores. John is interested in knowing if the average dollar amount per purchase is identical for the four stores. John randomly selected six receipts from each of the four stores:

a. Use SPSS to perform an ANOVA on this data.

b. What are the null and alternative hypotheses?

c. Is there support in this data for the notion that average dollar amount per purchase is the same for all stores?