spss assignment

Akhil rasad
poorexampleassignment1.pdf

Introduction[E1][E2]

The Theory of Planned Behavior was first explained by Ajzen (1985) [E3]which

implemented a pragmatic model explains human action and behavior. The theory

assumes how certain behavior occurs. The theory is interested in certain features

which explain people’s genuine behavioural selections. As reported by Ajzen (1985)

on his statement of planned behavior, that behaviour objectives are mainly directed by

three factors: a constructive or unconstructive attitudes towards certain behavior,

secondly subjective norm and lastly the perceived behavioral control. The theory is

illustrated in Figure (1). An attitude toward a behavior is recognized as an individual’s

positive or negative assessment of an appropriate behavior and is composed of an

individual’s salient beliefs regarding the perceived results of performing a behavior.

Subjective norm refers to an individual’s perception of whether significant referents

agree or disagree of a certain behavior. To identify the non-volitional feature of

behavior, the theory of planned behavior included an additional variable the perceived

behavioral control, which is not typically associated with traditional attitude

behavioral models (e.g., Fishbein and Ajzen 1975). The perceived behavioural control

describes the perceived difficulty level of performing the behavior referring both

previous experience and predictable difficulties. As a common rule, the more positive

the attitude toward performing a behavior, the superior the perceived social approval;

and the easier the performance of the behavior is perceived, the stronger the

behavioral intention.

Figure (1): The theory of planned behavior.[E4]

Analysis[l5]

As required in the coursework assignment details an analysis of the data is required to

show the sample profile, differences between the countries and the application of the

TPB. An analysis of the data was undertaken via SPSS and is included in the

appendix. [E6]

The sample profile.

The dataset provided data from two countries. A total sample of 248 participated.

150[E7] where from Greece. Of those who participated approximately [E8]37% were

female. Just over halve of the sample were 31 or under, therefore the sample

represents young people in each country.[E9] There was a substantial amount of

missing data for the question on income.[E10] Over 50% the sample were in full time

employment.[E11][E12]

Differences across the two countries: Greece and Spain

T-tests were conducted to establish if any differences in the means of intention,

attitude, SN and PBC were apparent across the two countries. The results in the

appendix show that there are differences with differences found for intention and

attitude but not for SN and PBC. Thus Greeks have lower intentions to quit smoking

and a more positive attitude towards smoking than respondents from Spain. [E13]

Regression analysis

A regression analysis was undertaken to identify what factors explain intention to quit

smoking. Data were pooled and analysed together. Results in the appendix show that

the TPB explained 34% of the variation in intention to quit smoking. However the

only significant TPB antecedent that significantly explained intention to quit was

PBC. [E14]

Discussion

The research was based on the TPB model which is pertinent to understanding the

smoking habits and behaviours of participants in the questionnaire. The model was

utilized to analyse the effects of attitudes, subjective norms and perceived behaviour

on individuals’ intentions to give up smoking. Our results recommend that the Theory

of Planned behavior significantly assists in the clarification of behavioral intention.

[E15] There is a significant amount of variation explained by perceived behavioral

control. Studies examining the TPB in similar context found that TPB components

accounted for a comparable amount of variance; Moan & Rise (2005) reported that

36% of variance was accounted for by the TPB constructs and Rise, Kovac, Kraft, &

Moan (2008) showed that 30% of variance was accounted for by the TPB constructs.

To summarise, the TPB is a good indicator of intention, but provides an incomplete

picture when applied in this context. Whilst it is obvious that intention cannot be

predicted completely accurately, there are a number of factors which, when included,

are likely to increase the success of the model. Attitude and subjective norm do not

present any effect in the regression model[E16]. The questions were about the

confident of stopping smoking and the probability of doing so within the next three

months[E17]. The results point out that there are other variables not been explained in

the theory which might influence the behavioral intention towards stopping

[E18]smoking. Suggestions for future research would be to incorporate some of these

other factors and [E19]investigate how much they affect an individual’s intention to

give up smoking. A good place to start would be to test gender and age as these have

been proven to have influences when applied to other TPB models.

The questionnaire was only accessible online, distributed through a government

smoking information website. The information gathered may be imbalanced because

it would generally attract participants who have internet access, computer knowledge

and time to search for the questionnaire. It is also filters potential participants,

because it would only be for individuals willing to give up smoking and show

initiative to search for the survey. This could give a false representation of the sample

profile of individuals willing to give up smoking[E20].

References

Make sure that you include a reference section using the Harvard style

Appendix[E21][E22]

Statistics[E23]

Country Gender Age Social position

Household

income

N Valid 248 246 243 247 177

Missing 0 2 5 1 71

Country[E24]

Frequency Percent Valid Percent

Cumulative

Percent

Valid Greece 150 60.5 60.5 60.5

Spain 98 39.5 39.5 100.0

Total 248 100.0 100.0

Gender

Frequency Percent Valid Percent

Cumulative

Percent

Valid Male 155 62.5 63.0 63.0

Female 91 36.7 37.0 100.0

Total 246 99.2 100.0

Missing System 2 .8

Total 248 100.0

Age[l25]

Frequency Percent Valid Percent

Cumulative

Percent

Valid 17 2 .8 .8 .8

18 3 1.2 1.2 2.1

19 6 2.4 2.5 4.5

20 6 2.4 2.5 7.0

21 2 .8 .8 7.8

22 6 2.4 2.5 10.3

23 6 2.4 2.5 12.8

24 9 3.6 3.7 16.5

25 14 5.6 5.8 22.2

26 4 1.6 1.6 23.9

27 9 3.6 3.7 27.6

28 7 2.8 2.9 30.5

29 8 3.2 3.3 33.7

30 13 5.2 5.3 39.1

31 12 4.8 4.9 44.0

32 10 4.0 4.1 48.1

33 7 2.8 2.9 51.0

34 7 2.8 2.9 53.9

35 5 2.0 2.1 56.0

36 7 2.8 2.9 58.8

37 3 1.2 1.2 60.1

38 4 1.6 1.6 61.7

39 10 4.0 4.1 65.8

40 7 2.8 2.9 68.7

41 5 2.0 2.1 70.8

42 5 2.0 2.1 72.8

43 6 2.4 2.5 75.3

44 3 1.2 1.2 76.5

45 11 4.4 4.5 81.1

46 7 2.8 2.9 84.0

47 3 1.2 1.2 85.2

48 3 1.2 1.2 86.4

49 2 .8 .8 87.2

50 6 2.4 2.5 89.7

51 1 .4 .4 90.1

52 2 .8 .8 90.9

53 1 .4 .4 91.4

54 2 .8 .8 92.2

55 3 1.2 1.2 93.4

56 2 .8 .8 94.2

57 1 .4 .4 94.7

58 1 .4 .4 95.1

59 3 1.2 1.2 96.3

60 1 .4 .4 96.7

61 1 .4 .4 97.1

62 1 .4 .4 97.5

63 1 .4 .4 97.9

64 1 .4 .4 98.4

65 2 .8 .8 99.2

68 1 .4 .4 99.6

69 1 .4 .4 100.0

Total 243 98.0 100.0

Missing System 5 2.0

Total 248 100.0

Social position

Frequency Percent Valid Percent

Cumulative

Percent

Valid in full time employment 128 51.6 51.8 51.8

in part time employment 15 6.0 6.1 57.9

unemployed 13 5.2 5.3 63.2

retired 7 2.8 2.8 66.0

a full time student 31 12.5 12.6 78.5

other 53 21.4 21.5 100.0

Total 247 99.6 100.0

Missing System 1 .4

Total 248 100.0

Household income

Frequency Percent Valid Percent

Cumulative

Percent

Valid 0 7 2.8 4.0 4.0

14 1 .4 .6 4.5

15 2 .8 1.1 5.6

16 1 .4 .6 6.2

17 1 .4 .6 6.8

20 1 .4 .6 7.3

30 2 .8 1.1 8.5

40 1 .4 .6 9.0

45 1 .4 .6 9.6

55 1 .4 .6 10.2

70 1 .4 .6 10.7

100 1 .4 .6 11.3

120 1 .4 .6 11.9

329 1 .4 .6 12.4

400 1 .4 .6 13.0

450 2 .8 1.1 14.1

500 1 .4 .6 14.7

600 1 .4 .6 15.3

650 1 .4 .6 15.8

700 8 3.2 4.5 20.3

800 4 1.6 2.3 22.6

900 2 .8 1.1 23.7

1000 5 2.0 2.8 26.6

1200 4 1.6 2.3 28.8

1350 1 .4 .6 29.4

1450 1 .4 .6 29.9

1500 4 1.6 2.3 32.2

1600 4 1.6 2.3 34.5

2000 8 3.2 4.5 39.0

2500 1 .4 .6 39.5

2700 1 .4 .6 40.1

2900 1 .4 .6 40.7

3000 2 .8 1.1 41.8

3600 1 .4 .6 42.4

4000 3 1.2 1.7 44.1

4500 1 .4 .6 44.6

5000 3 1.2 1.7 46.3

6000 1 .4 .6 46.9

7000 2 .8 1.1 48.0

7200 1 .4 .6 48.6

7500 1 .4 .6 49.2

8000 1 .4 .6 49.7

8400 1 .4 .6 50.3

9000 1 .4 .6 50.8

9500 1 .4 .6 51.4

10000 4 1.6 2.3 53.7

10800 1 .4 .6 54.2

10980 1 .4 .6 54.8

11000 2 .8 1.1 55.9

12000 8 3.2 4.5 60.5

13000 1 .4 .6 61.0

14000 4 1.6 2.3 63.3

15000 8 3.2 4.5 67.8

15500 1 .4 .6 68.4

17000 1 .4 .6 68.9

18000 6 2.4 3.4 72.3

20000 13 5.2 7.3 79.7

21000 1 .4 .6 80.2

22000 2 .8 1.1 81.4

25000 6 2.4 3.4 84.7

25500 1 .4 .6 85.3

27000 1 .4 .6 85.9

28000 1 .4 .6 86.4

30000 8 3.2 4.5 91.0

35000 3 1.2 1.7 92.7

38000 1 .4 .6 93.2

40000 2 .8 1.1 94.4

45000 2 .8 1.1 95.5

50000 2 .8 1.1 96.6

55000 1 .4 .6 97.2

60000 2 .8 1.1 98.3

90000 1 .4 .6 98.9

100000 1 .4 .6 99.4

450000 1 .4 .6 100.0

Total 177 71.4 100.0

Missing System 71 28.6

Total 248 100.0

Group Statistics

Country N Mean Std. Deviation Std. Error Mean

int_avg Greece 150 1.8713 1.32580 .10825

Spain 98 2.3944 .79431 .08024

att_avg Greece 150 -.1483 1.41615 .11563

Spain 98 -1.0612 1.51115 .15265

subjective norm - one item only Greece 150 1.46 1.535 .125

Spain 98 1.41 1.838 .186

se_avg Greece 150 3.3600 1.93703 .15816

Group Statistics

Country N Mean Std. Deviation Std. Error Mean

int_avg Greece 150 1.8713 1.32580 .10825

Spain 98 2.3944 .79431 .08024

att_avg Greece 150 -.1483 1.41615 .11563

Spain 98 -1.0612 1.51115 .15265

subjective norm - one item only Greece 150 1.46 1.535 .125

Spain 98 1.41 1.838 .186

se_avg Greece 150 3.3600 1.93703 .15816

Spain 98 3.6429 1.71410 .17315

Independent Samples Test[E26]

Levene's Test for Equality of

Variances t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

Mean

Difference

Std. Error

Difference

95% Confidence Interval of the

Difference

Lower Upper

int_avg Equal variances assumed 27.166 .000 -3.514 246 .001 -.52312 .14886 -.81632 -.22992

Equal variances not

assumed

-3.882 244.385 .000 -.52312 .13475 -.78853 -.25771

att_avg Equal variances assumed 2.364 .125 4.833 246 .000 .91290 .18890 .54083 1.28498

Equal variances not

assumed

4.767 197.843 .000 .91290 .19150 .53526 1.29054

subjective norm - one item

only

Equal variances assumed 1.963 .162 .240 246 .810 .052 .216 -.373 .477

Equal variances not

assumed

.231 181.107 .817 .052 .224 -.390 .494

se_avg Equal variances assumed 3.137 .078 -1.176 246 .241 -.28286 .24059 -.75675 .19103

Equal variances not

assumed

-1.206 224.600 .229 -.28286 .23451 -.74498 .17926

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .588 a .345 .337 .95424

a. Predictors: (Constant), se_avg, subjective norm - one item only,

att_avg

ANOVA b

Model Sum of Squares df Mean Square F Sig.

1 Regression 117.142 3 39.047 42.882 .000 a

Residual 222.182 244 .911

Total 339.324 247

a. Predictors: (Constant), se_avg, subjective norm - one item only, att_avg

b. Dependent Variable: int_avg

Coefficients a

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) .770 .142 5.426 .000

att_avg -.069 .041 -.090 -1.709 .089

subjective norm - one item

only

.017 .037 .024 .470 .638

se_avg .359 .033 .568 10.835 .000

a. Dependent Variable: int_avg