2. Research framework
Research problem - Factor affecting sales target
Research question - Why sales targets are not achieved in
telecom industry?
Data collection method - Questionnaire method
Dependent variable - Sales target
Independent variables:-
General mental ability
Job satisfaction
Effort
Sales experience.
Research hypothesis - Further Explained
3. Job satisfaction is positively related to sales
person performance.
Correlations
mean_job_sati
sfaction Sales Target Sales Target
mean_job_satisfaction Pearson Correlation 1 -.479** -.222**
Sig. (2-tailed) .000 .001
N 235 234 235
Sales Target Pearson Correlation -.479** 1 .458**
Sig. (2-tailed) .000 .000
N 234 234 234
Sales Target Pearson Correlation -.222** .458** 1
Sig. (2-tailed) .001 .000
N 235 234 235
**. Correlation is significant at the 0.01 level (2-tailed).
Ho: Accepted
4. Sales man with high job satisfaction have
high GMA
Independent Samples Test
Levene's Test for Equality
of Variances t-test for Equality of Means
95% Confidence Interval of
Sig. (2- Mean Std. Error the Difference
F Sig. t df tailed) Difference Difference Lower Upper
mean_job_satisfacti Equal variances 1.424 .234 -10.879 220 .000 -.95841 .08810 -1.13204 -.78478
on assumed
Equal variances not -10.450 117.115 .000 -.95841 .09172 -1.14005 -.77677
assumed
Ha: Accepted
5. With increase in salary job satisfaction increases.
ANOVA
mean_job_satisfaction
Sum of Squares df Mean Square F Sig.
Between Groups (Combined) 19.089 4 4.772 9.714 .000
Linear Term Unweighted 14.066 1 14.066 28.629 .000
Weighted 13.441 1 13.441 27.357 .000
Deviation 5.649 3 1.883 3.833 .010
Within Groups 113.000 230 .491
Total 132.089 234
Ha : Accepted
6. Person with high GMA have high
tendency to achieve sales target easily.
Chi-Square Tests
Asymp. Sig. (2-
Value df sided)
a
Pearson Chi-Square 59.183 16 .000
Likelihood Ratio 58.726 16 .000
Linear-by-Linear 22.593 1 .000
Association
N of Valid Cases 233
a. 12 cells (48.0%) have expected count less than 5. The minimum
expected count is .04.
Ho : Accepted
7. Job satisfaction can be achieved by putting
high efforts.
b
ANOVA
Model Sum of Squares df Mean Square F Sig.
a
1 Regression 68.881 2 34.441 126.413 .000
Residual 63.207 232 .272
Total 132.089 234
a. Predictors: (Constant), Effort, Effort
b. Dependent Variable: mean_job_satisfaction
Ha : Accepted
b
Model Summary
Change Statistics
Adjusted R Std. Error of the R Square
Model R R Square Square Estimate Change F Change df1 df2 Sig. F Change
a
1 .722 .521 .517 .52196 .521 126.413 2 232 .000
a. Predictors: (Constant), Effort, Effort
b. Dependent Variable: mean_job_satisfaction