Working with SPSS (PASW) Software
It is certainly a clich� that we are living in a �global world� and as such the concept of �global leadership� may be seen to be a somewhat nebulous one but the reality is that there is increasingly greater communication on a global scale and leaders need to cope with this. Morrison (2012) seems to suggest that MNEs � presumably Western ones � do not recognise the extent to which leadership skills on a global basis need to be developed and as such may have a poor understanding of how to develop them. Please see the attached article and think of suggestions for improvement.
please read the attached file:
Morrison, C., (2012), Global leadership development: a case of misplaced optimism? People & Strategy. Vol. 35 Issue 2, p18-20.
Lesson 22 Problem 1-4
Question 1.
The total score in this case is the number of items the pupils answered correctly i.e. scored a 1 out of the eight-item algebra test. The total score can be used to assess the effectiveness of the new algebra teaching method. If the pupils’ total scores are high, then we can conclude that the new involvement technique is an effective method for teaching algebra to first graders (Ghauri, et al. 2005). On the other hand if most of the pupils score a 0 in most items and thus a low total score, we then conclude that the involvement technique is not an effective method of teaching algebra to first graders. To compute the total score in SPSS, we use the “compute variable” option found under “transform” in the menu bar (Kumar, 2009). To do this we select “transform” from the menu bar, then select “compute variable” from the drop down list. You then enter “total score” under target variable in the dialogue box. Under the numeric expression in the dialogue box, enter item1 + item2 + item3 + item4 + item5 + item6 + item7 + item8 and click ok (Creswell, 2003). From the data view window, a new variable, “total score” is inserted in the right hand side. The computed values are;
8
6
5
7
4
6.
This are the scores that the six students scored in the 8 questions four choices test.
Question 2.
The test value for this problem is 2. The value 2 was obtained by factoring in the probability of a pupil scoring a 1, in each item out of 4 choices given and multiplying it by the number of items they were to answer.
This equation gives as a statistical test value.
Question 3.
The SPSS output for one sample t-test is as shown in table 1 and table 2 below
| One-Sample Statistics | ||||
| N | Mean | Std. Deviation | Std. Error Mean | |
| Total scores | 6 | 6.00 | 1.414 | .577 |
Table 1
| One-Sample Test | ||||||
| Test Value = 2 | ||||||
| t | df | Sig. (2-tailed) | Mean Difference | 95% Confidence Interval of the Difference | ||
| Lower | Upper | |||||
| Total scores | 6.928 | 5 | .001 | 4.000 | 2.52 | 5.48 |
Table 2
From table 1 above, the mean algebra score is 6.00 with a standard deviation of 1.414. The t-test value is 6.928 as shown in table 2 while the p value is 0.001.
Question 4.
Hypothesis
H0: The total score is not significantly different from 2 i.e. Total score=2
Decision Rule
Reject H0if (Creswell, 2003). From table 2 above, p value = 0.001 which is less than 0.05 hence we reject the null hypothesis.
Conclusion
We can conclude that the new involvement technique is not an effective method for teaching algebra to first graders at 95% level of precision.
Lesson 23 Problem 1-5
Question 1.
The total index of life stress (ILS) score is the average of interpersonal life stress and occupational life stress for a specific woman at a given age (Cooper & Schindler, 2011). In this case it is the average of the interpersonal life stress of a given woman at the age of 40/60 years and her occupational life stress at the age of 40/60. To compute the total index of life stress (ILS) in SPSS, we use the “compute variable” option found under “transform” in the menu bar. To do this we select “transform” from the menu bar, then select “compute variable” from the drop down list. You then enter “total index of life stress (ILS) 40/60” under target variable in the dialogue box. Under the numeric expression in the dialogue box, enter (inter_40 + occup_40) / 2 for total index of life stress (ILS) for women aged 40 years and enter (inter_60+ occup_60) / 2 for women aged 60 .and click ok. From the data view window, a new variables, “total index of life stress (ILS) 40” and “total index of life stress (ILS) 60” are created and inserted in the right hand side. The computed values are;
| index of life stress (ILS) at age 40 | index of life stress (ILS) at age 60 |
| 72.5 83.0 85.5 77.5 82.5 64.5 58.0 75.5 83.0 83.5 73.0 82.0 81.5 85.0 67.5 77.0 83.5 76.5 76.5 85.0 76.5 81.0 79.5 83.0 86.5 74.0 84.5 66.5 76.5 80.5 67.5 73.5 72.5 73.5 61.0 78.0 77.0 71.5 74.0 69.5 63.0 66.0 66.5 80.0 81.5 | 74.0 69.5 71.5 61.5 66.0 70.0 73.5 72.0 69.0 70.5 67.0 75.0 78.5 70.0 63.5 66.5 67.0 79.5 68.5 67.0 64.0 77.0 60.5 65.0 74.5 64.0 60.0 67.0 72.0 64.0 67.5 77.5 65.0 65.0 62.5 69.0 72.5 66.0 62.5 69.0 75.5 67.5 64.0 62.5 65.5 |
Source: SPSS ouput
Question 2.
| Paired Samples Test | |||||||||
| Paired Differences | t | df | Sig. (2-tailed) | ||||||
| Mean | Std. Deviation | Std. Error Mean | 95% Confidence Interval of the Difference | ||||||
| Lower | Upper | ||||||||
| Pair 1 | ILS_40 – ILS_60 | 7.489 | 8.633 | 1.287 | 4.895 | 10.083 | 5.819 | 44 | .000 |
Table 2
Hypothesis
H0: On average, life stress does not change with age in the population.
Decision Rule
Reject H0 if . From table 2 above, p value = 0.000 which is less than 0.05 hence we reject the null hypothesis.
Conclusion
We can conclude that the overall life stress on average increases or decreases with age in the population at 95% level of precision.
Question 3.
The changes in life stress from 40 years of age to 60 years of age is computed as the difference between life stress at 60years of age and life stress at 40years of age. This difference can show either an increase or a decrease in life stress with age. To compute the changes in life stress from 40 years of age to 60 years of age in SPSS, we use the “compute variable” option found under “transform” in the menu bar. To do this we select “transform” from the menu bar, then select “compute variable” from the drop down list. You then enter “change in life stress” under target variable in the dialogue box. Under the numeric expression in the dialogue box, enter (ILS_60 – ILS_40) and click ok. From the data view window, a new variable, “change in life stress” is created and inserted in the right hand side. The computed values are;
| Change in Life Stress |
| 1.5 -13.5 -14.0 -16.0 -16.5 5.5 15.5 -3.5 -14.0 -13.0 -6.0 -7.0 -3.0 -15.0 -4.0 -10.5 -16.5 3.0 -8.0 -18.0 -12.5 -4.0 -19.0 -18.0 -12.0 -10.0 -24.5 0.5 -4.5 -16.5 0.0 4.0 -7.5 -8.5 1.5 -9.0 -4.5 -5.5 -11.5 -0.5 12.5 1.5 -2.5 -17.5 -16.0 |
| Question 4. Paired Samples Test | |||||||||
| Paired Differences | t | df | Sig. (2-tailed) | ||||||
| Mean | Std. Deviation | Std. Error Mean | 95% Confidence Interval of the Difference | ||||||
| Lower | Upper | ||||||||
| Pair 1 | Interpersonal life stress at age 40 – Interpersonal life stress at age 60 | 3.200 | 13.942 | 2.078 | -.989 | 7.389 | 1.540 | 44 | .131 |
| Pair 2 | Occupational life stress at age 40 – Occupational life stress at age 60 | 11.778 | 12.696 | 1.893 | 7.964 | 15.592 | 6.223 | 44 | .000 |
Table 3
Hypothesis
H0: On average, Interpersonal life stress does not change with age in the population.
H0: On average, Occupational life stress does not change with age in the population.
Decision Rule
Reject H0 if (Creswell, 2003). From table 3 above, p value forInterpersonal life stress = 0.131 which is greater than 0.05 hence we accept the null hypothesis. On the other hand, the p value for occupational life stress = 0.000 which is less than 0.05 hence we reject the null hypothesis.
Conclusion
We can conclude that Interpersonal life stress does not change with age while occupational life stress changes with age at 95% level of precision
Question 5.
A paired-samples t test was conducted to evaluate whether on average, life stress changes with age in the population. The results indicated that the in index life stress at 40 (M = 75.92, SD =7.242) was significantly different from index of life stress at 60 years of age (M = 68.43, SD = 4.974), t(44) = 5.819, p< .01. The overall life stress on average increases or decreases with age in the population at 95% level of precision where 95% confidence interval for the mean difference between the two ages was 4.895 to 10.083.
| Paired Samples Statistics | |||||
| Mean | N | Std. Deviation | Std. Error Mean | ||
| Pair 1 | ILS_40 | 75.92 | 45 | 7.242 | 1.080 |
| ILS_60 | 68.43 | 45 | 4.974 | .742 |
Table 4.
A paired-samples t test was conducted to evaluate whether interpersonal life stress at age 40 and interpersonal life stress at age 60 were different. From the results, it can be observed that the interpersonal life stress at age 40 (M = 78.20, SD =11.655) was not significantly different from interpersonal life stress at 60 years of age (M = 75.00, SD = 7.711), t(44) = 1.540, p> .05 i.e. 0.131. According to Creswell (2003), with a p value (0.131) greater than alpha (0.05) we reject the alternative hypothesis that there is a significant difference between interpersonal life stress at 60 years and at 40 years. The Interpersonal life stress does not change with age in the population at 95% level of precision where 95% confidence interval for the mean difference between the two ages was -0.989 to 7.389. Another paired-samples t test was conducted to evaluate whether interpersonal life stress at age 40 and occupational life stress at age 60 were different. From the results of the analysis, it can be observed that the occupational life stress at age 40 (M = 73.64, SD =9.547) was significantly different from occupational life stress at age 60(M = 61.87, SD = 6.625), t(44) = 6.223, p< .01 i.e. 0.000. The occupational life stress changes with age in the population at 95% level of precision where 95% confidence interval for the mean difference between the two ages was 1.893 to 7.964.
