Question

In: Statistics and Probability

The following data are from an experiment designed to investigate the perception of corporate ethical values...

The following data are from an experiment designed to investigate the perception of corporate ethical values among individuals who are in marketing. Three groups are considered: management, research and advertising (higher scores indicate higher ethical values).

Marketing Managers Marketing Research Advertising
6 8 6
5 8 7
4 7 6
5 7 5
6 8 6
4 7 6
  1. Compute the values identified below (to 1 decimal, if necessary).
    Sum of Squares, Treatment
    Sum of Squares, Error
    Mean Squares, Treatment
    Mean Squares, Error

  2. Use  = .05 to test for a significant difference in perception among the three groups.

    Calculate the value of the test statistic (to 2 decimals).


    c. The p-value is Selectless than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 6

    What is your conclusion?
    Select : Conclude the mean perception scores for the three groups are not all the same or Cannot conclude there are differences among the mean perception scores for the three groups
  3. Using  = .05, determine where differences between the mean perception scores occur.

    Calculate Fisher's LSD value (to 2 decimals).


    Test whether there is a significant difference between the means for marketing managers (1), marketing research specialists (2), and advertising specialists (3).
    Difference Absolute Value Conclusion
    x 1 - x2 Select Significant difference No significant differenceItem 10
    x1 - x3 Select Significant difference No significant differenceItem 12
    x 2 - x3

Solutions

Expert Solution

using minitab>stat>ANOVA
we have

One-way ANOVA: Marketing Managers, Marketing Research, Advertising

Method

Null hypothesis All means are equal
Alternative hypothesis At least one mean is different
Significance level α = 0.05

Equal variances were assumed for the analysis.


Factor Information

Factor Levels Values
Factor 3 Marketing Managers, Marketing Research, Advertising


Analysis of Variance

Source DF Seq SS Contribution Adj SS Adj MS F-Value P-Value
Factor 2 19.000 71.70% 19.000 9.5000 19.00 0.000
Error 15 7.500 28.30% 7.500 0.5000
Total 17 26.500 100.00%


Model Summary

S R-sq R-sq(adj) PRESS R-sq(pred)
0.707107 71.70% 67.92% 10.8 59.25%


Means

Factor N Mean StDev 95% CI
Marketing Managers 6 5.000 0.894 (4.385, 5.615)
Marketing Research 6 7.500 0.548 (6.885, 8.115)
Advertising 6 6.000 0.632 (5.385, 6.615)

Pooled StDev = 0.707107


Fisher Pairwise Comparisons

Grouping Information Using the Fisher LSD Method and 95% Confidence

Factor N Mean Grouping
Marketing Research 6 7.500 A
Advertising 6 6.000 B
Marketing Managers 6 5.000 C

Means that do not share a letter are significantly different.


Fisher Individual Tests for Differences of Means

Difference SE of Adjusted
Difference of Levels of Means Difference 95% CI T-Value P-Value
Marketing Re - Marketing Ma 2.500 0.408 ( 1.630, 3.370) 6.12 0.000
Advertising - Marketing Ma 1.000 0.408 ( 0.130, 1.870) 2.45 0.027
Advertising - Marketing Re -1.500 0.408 (-2.370, -0.630) -3.67 0.002

Simultaneous confidence level = 88.31%

  1. Compute the values identified below (to 1 decimal, if necessary).
    Sum of Squares, Treatment 19
    Sum of Squares, Error 7.5
    Mean Squares, Treatment 9.5
    Mean Squares, Error 0.5
  2. Use  = .05 to test for a significant difference in perception among the three groups.

    the value of the test statistic is 19.00


    c. The p-value is less than .01

    What is your conclusion?
    Conclude the mean perception scores for the three groups are not all the same
  3. Using  = .05, determine where differences between the mean perception scores occur.

    Fisher's LSD value is 0.41


    Test whether there is a significant difference between the means for marketing managers (1), marketing research specialists (2), and advertising specialists (3).
    Difference Absolute Value Conclusion
    x 1 - x2 6.12 significant difference
    x1 - x3 2.44 significant difference
  4. x 2 - x3 3.67 significant difference

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