Read the article about creating Likert scales. You will be creating 8 different
ID: 3300684 • Letter: R
Question
Read the article about creating Likert scales. You will be creating 8 different scales: work, pay, supervision, co-worker, opportunities, Overall independent, engagement and commitment. Each scale is the average of the items within the dimension. For example, the work scale will be the average of the four items, W1 – W4, for each observation; Overall Independent is the average of the twenty independent variables for each observation (W1 – O4). Cut and paste (you will need to use the paste special option) until you have a clean data set that looks like the following:
Observation
Gender
Age
Education
Level
Work
Pay
Supervision
Co-worker
Opportunities
Overall independent
Engagement
Commitment
Overall
1
M
30
B
N
2.5
3.75
2.5
2.25
3
2.8
3.75
2.5
6
2
F
28
A
H
2.25
3
3
4
2.25
2.9
2.25
2.25
4
I recommend that you keep a “clean” copy of this revised/scaled data set saved separately. You will need to sort the data several times for the following analyses. Begin each analysis with a newly copied version of the scaled data set. Remember, when you sort the data to sort ALL of the data set, not just the variable of interest.
Descriptive Analysis: Describe the data using basic statistics and percentages. For example, 64% of the observations are Male. The average Overall Satisfaction rating (dependent) is 6.58. Etc. Be thorough and use charts, graphs, and tables. Discuss your findings.
Correlation analysis: Determine the correlation between each of the 6 independent measures and the three dependent measures (Work & engagement, work & commitment, work & overall, etc). Also, compute the correlation between age and the three dependent variables. Discuss your results.
Gender analysis: Is there a statistically significant difference between the genders? Use Excel’s t-test function to test for differences in each of the 9 variables. This will be a two-tailed hypothesis test: Ho: Wf - Wm = 0; Ha: Wf – Wm 0. In case you’ve forgotten how to use the Excel function, there’s an illustration below. Discuss your results.
Age analysis: Is there a statistically significant difference between age and the dependent variables? Sort each of the dependent data columns into the following age groups: 29, 30-39, 40-49, 50-59, and 60-69. Use Excel’s Anova-Single Factor to determine if there is a statistically significant difference across ages. Use the example below (for engagement) to set up your data for analysis. Discuss your results.
29
30-39
40-49
50-59
60-69
2.5
3.75
4.25
5
5
2.5
3.75
4.25
5
4.25
2.5
2.25
4.25
5
Etc.
Etc.
Etc.
Etc.
Education analysis: Can we conclude that there is a statistically significant difference between level of education and the dependent variables? Sort and set up the data as you did for the age analysis. Initially, conduct an Anova analysis to determine if there is a difference across education levels. If there is, then test the following null hypotheses (t-test): Es-Eh 0; Ea-Eh 0; Eb-Eh 0; Eb-Ea 0; Eg-Eb 0 (see the t-test in problem 3). Discuss your results. Comment on whether education level appears to be positively or negatively correlated to each dependent variable.
Employment Level analysis: Repeat the analysis above (ANOVA) using level of employment as the categorical variable. Use comparable pairings for the t-tests. Comment on whether employment level appears to be positively or negatively correlated to each dependent variable.
Interdependence: Create a 3 x 2 matrix by further categorizing the variables. For the dependent variable, Engagement, create two categories: unengaged and fully engaged. Code the data as follows: U if the value is < 3.5; E if the value is 3.5. Pick an independent variable (other than overall because it is used below) and code it as follows: L (low) if it is < 3; M (medium)if it is equal to or above 3 but less than 4; H(high) if it is 4. Once you have the data coded, organize it into a contingency table. You can use Excel’s pivot table to do this, but if you are unfamiliar with how the function works, it might be faster to manually count the number of times that you see an M and an E together, for example. The table below illustrates the steps and final table you will need. You are finally ready to do some analysis! Conduct a chi-squared analysis to determine if the dependent variable, Engagement, is independent from the independent variable you have chosen. You will need to repeat this analysis with the other dependent variable, Commitment, but you can use the same independent variable. Code Commitment as follows: N (for not committed) if the value is < 3; C if the value is 3. Discuss your results.
Observation
Overall Indpdnt
Engagement
Overall Indpdnt
Engagement
1
2.8
3.75
H
E
E
U
2
2.9
2.25
H
E
L
10
31
3
3.55
4.25
H
E
M
39
8
4
3.75
5
H
E
H
16
0
Conclusions: Summarize what you learned from the above analyses about Job Satisfaction, its dimensions and its relationship to engagement, commitment, and overall perceived satisfaction.
Employee Demographics Work Independent Variable Pay Independent Variable Supervision Independent Variable Co-workers Independent Variable Opportunities Independent Variable Engagement Dependent Variable Commitment Dependent Variable Dependent Observation Gender Age Education Level W1 W2 W3 W4 P1 P2 P3 P4 S1 S2 S3 S4 CW1 CW2 CW3 CW4 O1 O2 O3 O4 E1 E2 E3 E4 C1 C2 C3 C4 Overall 1 M 30 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 2 F 28 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 4 3 M 40 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 4 F 41 G LM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 9 5 M 45 B EM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 8 6 F 36 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 4 7 F 34 B MM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 7 8 M 24 H H 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 6 9 M 27 H H 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 6 10 M 55 G MM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 8 11 F 28 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 4 12 M 43 B LM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 13 F 41 G MM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 8 14 F 45 B EM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 8 15 M 30 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 16 M 28 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 4 17 M 37 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 7 18 M 41 G MM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 9 19 F 61 B EM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 8 20 F 36 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 4 21 M 34 B LM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 7 22 M 25 H H 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 8 23 M 32 H H 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 6 24 M 55 G MM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 8 25 F 29 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 4 26 M 44 B LM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 27 M 41 G MM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 7 28 F 31 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 29 F 32 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 5 30 M 38 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 7 31 M 43 G MM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 8 32 M 57 B EM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 7 33 F 41 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 5 34 F 37 B LM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 7 35 M 23 H H 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 6 36 M 26 H H 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 6 37 M 58 G LM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 8 38 M 43 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 39 M 49 G EM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 7 40 F 29 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 41 F 30 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 3 42 M 40 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 7 43 F 32 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 5 44 M 28 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 5 45 F 44 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 7 46 M 51 G EM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 8 47 F 45 B MM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 6 48 F 36 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 5 49 M 34 B MM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 6 50 M 27 H LM 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 7 51 F 24 H H 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 8 52 M 55 G MM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 7 53 F 31 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 5 54 M 28 S H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 3 55 M 43 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 56 M 41 G MM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 7 57 F 45 B LM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 8 58 M 41 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 3 59 M 34 B MM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 7 60 M 23 H H 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 8 61 F 31 H LM 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 6 62 M 54 G MM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 8 63 F 42 B N 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 64 M 49 G EM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 7 65 M 33 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 66 M 28 H H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 4 67 F 40 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 68 M 31 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 69 M 28 H H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 5 70 F 46 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 71 M 33 G N 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 8 72 M 45 B MM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 7 73 M 31 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 5 74 F 44 B LM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 6 75 M 25 H H 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 7 76 M 27 H H 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 6 77 M 60 G MM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 8 78 F 28 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 5 79 F 48 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 80 M 51 G MM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 9 81 M 39 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 82 M 28 H H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 5 83 F 39 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 7 84 M 59 G EM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 8 85 M 45 B MM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 8 86 F 37 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 5 87 F 44 B MM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 7 88 M 28 H H 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 6 89 M 26 H H 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 6 90 M 59 G EM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 8 91 M 40 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 7 92 F 41 G N 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 8 93 F 30 B N 3 2 2 3 4 3 4 4 3 3 2 2 2 2 3 2 4 2 3 3 4 4 3 4 3 2 3 2 6 94 M 28 S H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 5 95 M 40 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 96 M 28 A H 2 2 2 3 3 2 3 4 3 2 4 3 4 4 4 4 2 2 3 2 3 2 2 2 2 2 3 2 4 97 M 40 B MM 4 5 4 4 3 4 4 4 4 3 3 4 3 4 3 3 4 2 3 3 4 4 4 5 4 3 5 4 8 98 M 41 G EM 5 5 5 4 3 4 5 4 4 4 4 3 3 4 3 3 4 3 3 2 5 5 5 5 4 3 4 5 8 99 F 45 B EM 4 4 4 4 3 4 3 4 5 5 4 5 5 5 4 4 5 2 3 4 5 4 4 4 4 3 4 3 7 100 M 36 B N 4 3 3 3 3 3 4 4 2 2 2 2 3 3 3 2 3 4 3 2 4 2 2 3 2 1 2 2 5 101 F 34 B MM 4 4 3 4 3 4 4 5 3 3 4 4 3 4 3 3 4 3 4 4 4 4 4 4 4 3 3 4 7 102 M 24 H H 3 2 3 2 4 3 4 5 3 3 4 4 4 4 4 4 3 4 3 2 3 3 2 2 4 2 2 3 6 103 M 27 H LM 2 3 2 3 2 2 3 4 2 2 3 2 4 4 4 4 4 4 3 2 3 3 2 3 3 2 3 4 7 104 M 56 G MM 5 5 4 5 4 5 4 5 5 5 4 5 4 4 4 4 5 2 4 3 5 5 5 5 5 4 5 5 8Explanation / Answer
Work Pay Supervision Co worker Opportunities Overall independent Engagement Commitment
Mean 2.375 3.375 2.75 3.125 2.625 2.85 3 2.375
Standard Error 0.125 0.375 0.25 0.875 0.375 0.05 0.75 0.125
Median 2.375 3.375 2.75 3.125 2.625 2.85 3 2.375
Mode #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A
Standard Deviation 0.176776695 0.530330086 0.353553391 1.237436867 0.530330086 0.070710678 1.060660172 0.176776695
Sample Variance 0.03125 0.28125 0.125 1.53125 0.28125 0.005 1.125 0.03125
Kurtosis #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!
Skewness #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!
Range 0.25 0.75 0.5 1.75 0.75 0.1 1.5 0.25
Minimum 2.25 3 2.5 2.25 2.25 2.8 2.25 2.25
Maximum 2.5 3.75 3 4 3 2.9 3.75 2.5
Sum 4.75 6.75 5.5 6.25 5.25 5.7 6 4.75
Count 2 2 2 2 2 2 2 2
Largest(1) 2.5 3.75 3 4 3 2.9 3.75 2.5
Smallest(1) 2.25 3 2.5 2.25 2.25 2.8 2.25 2.25
Anova: Single Factor
SUMMARY
Groups Count Sum Average Variance
Column 1 3 7.5 2.5 0
Column 2 3 9.75 3.25 0.75
Column 3 3 12.75 4.25 0
Column 4 3 15 5 0
Column 5 2 9.25 4.625 0.28125
ANOVA
Source of Variation SS df MS F P-value F crit
Between Groups 12.1875 4 3.046875 15.39474 0.000465 3.633089
Within Groups 1.78125 9 0.197917
Total 13.96875 13
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