MULTIVARIATE STATISTICS

Multivariate Statistics



Multivariate Statistics

Hypotheses

HO 1: There is a correlation between education and salary of the participants.

HO 2: There is an association between age of the participants and education of the participants.

HO 3: There is an association between age of the participants and their salary.

HO: There is an association between age of the participants and the level of English of the participants.

HO 4: There is a relationship of cambridge face memory test with the trustworthiness average time taken.

HO 5: There is a relationship of cambridge face memory test with the aggressiveness average time taken.

HO 6: There is a relationship of cambridge face memory test with the angry expression average time taken.

HO 7: There is a relationship of cambridge face memory test with the happy expression average time taken.

HO 8: There is a relationship of cambridge face memory test with the identity average time taken.

HO 9: There is a relationship of cambridge face memory test with the face detection.

Descriptive Statistics

From the given descriptive table, it can be observed that the average age of the respondents is 33, with the minimum age of 18 and maximum age of 73. Thus, it is found that the age range of the respondents is 55. Moreover, it is found that the mean values of trustworthiness AvgCorrect and Aggressiveness AvgCorrect are 0.65 and 0.58 with less deviation of 0.097 and 0.08. The descriptive statistics are the basic statistical measures that are used for summarizing the whole data set into meaningful indicators. It provides simplified summaries of the measures and sample. Besides it, Angry Expression AvgCorrect is 0.74 with the standard deviation of 0.11. With the help of descriptive statistics, it is very simple to describe what the trend of the data. Moreover, with the help of inferential statistics, the statisticians aim to draw the results of data as it presents the key aspects that are statistics. For case in point, the inferential statistics is used to extrapolate the data from a population that shows the key aspects of the selected sample from the target population. Moreover, the inferential statistics is also used in order to make decisions about the possibility of a significant difference between the groups which is a reliable or could have occurred by possibility. For that reason, the inferential statistics is used in order to conclude the results from the collected data and generalize these inferences to the whole population. Thus, the descriptive statistics is simply used in order to explain the important characteristics of data. In addition to this, the mean value of Happy Expression AvgCorrect is 0.65 with the less deviation in the data that is 0.111. Keeping this in view, it can be said that the data trend shows less deviation.

Descriptive Statistics

N

Range

Minimum

Maximum

Sum

Mean

Std. Deviation

Variance

Statistic

Statistic

Statistic

Statistic

Statistic

Statistic

Std. Error

Statistic

Statistic

Age

375

55

18

73

12240

32.64

.581

11.249

126.541

Trustworthiness_AvgCorrect

375

.5778

.3000

.8778

2.4686E2

.658281

.0050299

.0974028

.009

Trustworthiness_AvgTimeTaken

375

33.7530

6.8261

40.5791

8.3375E3

2.223345E1

.3655047

7.0779683

50.098

Aggressiveness_AvgCorrect

375

.5222

.2667

.7889

2.2118E2

.589808

.0041912

.0811631

.007

Aggressiveness_AvgTimeTaken

375

38.9187

6.5956

45.5143

8.5514E3

2.280377E1

.3703976

7.1727189

51.448

Angry Expression_AvgCorrect

375

.7111

.2667

.9778

2.8093E2

.749157

.0056823

.1100381

.012

Angry Expression_AvgTimeTaken

375

37.2908

7.6028

44.8936

9.2061E3

2.454947E1

.3804696

7.3677630

54.284

Happy Expression_AvgCorrect

375

.5889

.3111

.9000

2.4473E2

.652621

.0057575

.1114935

.012

Happy Expression_AvgTimeTaken

375

36.3276

7.7422

44.0698

9.1459E3

2.438900E1

.4057880

7.8580499

61.749

Identity_AvgCorrect

375

.6389

.2917

.9306

2.5560E2

.681593

.0056855

.1100994

.012

Identity_AvgTimeTaken

375

34.7899

8.7678

43.5576

9.5829E3

2.555427E1

.3944619

7.6387216

58.350

CFMT_AvgScore

375

.5556

.4444

1.0000

2.8610E2

.762925

.0067422

.1305620

.017

CFMT_AvgRTCorrect

375

7.2830

1.1130

8.3960

9.8258E2

2.620205E0

.0491876

.9525140

.907

Face_Detection_Score

375

.5667

.4333

1.0000

2.9810E2

.794930

.0053199

.1030194

.011

Face_Detection_AvgRTCorrect

375

2.7344

.4511

3.1855

4.9356E2

1.316147E0

.0136696

.2647115

.070

ATTENTIONAL_1

375

3

1

4

919

2.45

.052

1.006

1.013

ATTENTIONAL_2

375

3

1

4

1127

3.01

.045

.862

.743

ATTENTIONAL_3

375

3

1

4

1033

2.75

.046

.889

.790

ATTENTIONAL_4

375

3

1

4

1083

2.89

.048

.938

.880

ATTENTIONAL_5

375

3

1

4

1034

2.76

.049

.943

.890

ATTENTIONAL_6

375

3

1

4

892

2.38

.055

1.060

1.124

ATTENTIONAL_7

375

3

1

4

1029

2.74

.048

.924

.854

ATTENTIONAL_8

375

3

1

4

829

2.21

.050

.960

.921

ATTENTIONAL_9

375

3

1

4

1069

2.85

.050

.964

.930

ATTENTIONAL_10

375

3

1

4

1166

3.11

.041

.792

.627

ATTENTIONAL_11

375

3

1

4

1070

2.85

.041

.793

.628

ATTENTIONAL_12

375

3

1

4

1187

3.17

.045

.862

.743

Valid N (listwise)

375

The Correlation Analysis

Correlations

Education

Salary

Education

Pearson Correlation

1

.254 **

Sig. (2- tailed)

.000

N

375

375

Salary

Pearson Correlation

.254 **

1

Sig. (2- tailed)

.000

N

375

375

**. Correlation is significant at the 0.01 level (2- tailed).

From the above table, it can be observed that there is correlation between the variables that are education and salary as the ...