How can we interpuret the data into plain English? If the Question is : What cha

Question

How can we interpuret the data into plain English?

If the Question is :

What characteristics are associated with salary?

And we found the following characteristics are associated with the salary.

1.2a Salary and No. of years worked – Correlation Linear

1.2b Salary and position - ANOVA
1.2c Salary and minority status - Independent Sample T-test

1.2d Salary and sex - Independent Sample T-test

1.2e Salary and Formal education – Correlation

Where the output SPSS is as the following.

How can we interpret the data into plain English. Please highlight the data that we should pay attention to.

Correlations

annual_sal

yr_work

annual_sal

Pearson Correlation

1

-.084

Sig. (2-tailed)

.067

N

474

474

yr_work

Pearson Correlation

-.084

1

Sig. (2-tailed)

.067

N

474

474

1.2b

Oneway

Descriptives

annual_sal

N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Mean

Minimum

Maximum

Lower Bound

Upper Bound

1 Clerical

363

$55,677.08

$15,135.990

$794.433

$54,114.80

$57,239.36

$31,500

$160,000

2 Custodial

27

$61,877.78

$4,229.233

$813.916

$60,204.75

$63,550.81

$48,600

$70,500

3 Manager

84

$127,955.60

$36,489.552

$3,981.337

$120,036.88

$135,874.31

$68,820

$270,000

Total

474

$68,839.14

$34,151.323

$1,568.622

$65,756.80

$71,921.47

$31,500

$270,000

ANOVA

annual_sal

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

357753935700.000

2

178876967900.000

434.481

.000

Within Groups

193912046000.000

471

411702857.800

Total

551665981700.000

473

Post Hoc Tests

Multiple Comparisons

Dependent Variable:   annual_sal

Bonferroni

(I) position

(J) position

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

1 Clerical

2 Custodial

-$6,200.698

$4,047.520

.379

-$15,925.12

$3,523.72

3 Manager

-$72,278.515*

$2,456.704

.000

-$78,180.90

-$66,376.13

2 Custodial

1 Clerical

$6,200.698

$4,047.520

.379

-$3,523.72

$15,925.12

3 Manager

-$66,077.817*

$4,488.817

.000

-$76,862.48

-$55,293.16

3 Manager

1 Clerical

$72,278.515*

$2,456.704

.000

$66,376.13

$78,180.90

2 Custodial

$66,077.817*

$4,488.817

.000

$55,293.16

$76,862.48

*. The mean difference is significant at the 0.05 level.

1.2c

T-Test

Group Statistics

minority

N

Mean

Std. Deviation

Std. Error Mean

annual_sal

0 "Non-minority"

370

$72,046.62

$36,088.191

$1,876.136

1 "Minority"

104

$57,427.88

$22,843.275

$2,239.967

Independent Samples Test

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

annual_sal

Equal variances assumed

28.487

.000

3.915

472

.000

$14,618.737

$3,734.222

$7,280.981

$21,956.493

Equal variances not assumed

5.003

262.188

.000

$14,618.737

$2,921.873

$8,865.415

$20,372.059

1.2d

T-Test

Group Statistics

sex

N

Mean

Std. Deviation

Std. Error Mean

annual_sal

0 "Male"

258

$82,883.57

$38,998.427

$2,427.936

1 Female

216

$52,063.84

$15,116.043

$1,028.516

Independent Samples Test

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

annual_sal

Equal variances assumed

119.669

.000

10.945

472

.000

$30,819.723

$2,815.813

$25,286.644

$36,352.803

Equal variances not assumed

11.688

344.262

.000

$30,819.723

$2,636.801

$25,633.455

$36,005.991

1.2e

Correlations

Correlations

annual_sal

highest

annual_sal

Pearson Correlation

1

.661**

Sig. (2-tailed)

.000

N

474

474

highest

Pearson Correlation

.661**

1

Sig. (2-tailed)

.000

N

474

474

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

Correlations

annual_sal

yr_work

annual_sal

Pearson Correlation

1

-.084

Sig. (2-tailed)

.067

N

474

474

yr_work

Pearson Correlation

-.084

1

Sig. (2-tailed)

.067

N

474

474

Explanation / Answer

Answer:

How can we interpuret the data into plain English?

If the Question is :

What characteristics are associated with salary?

And we found the following characteristics are associated with the salary.

1.2a Salary and No. of years worked – Correlation Linear

Correlation between Salary and No. of years worked is -0.084, P=0.067 which is > 0.05 level. Correlation is not significant.

1.2b Salary and position – ANOVA

ANOVA result of average salary comparison 3 levels of position shows that F= 434.481, P=0.000 which is <0 .05 level. Position is significantly affect salary.

1.2c Salary and minority status - Independent Sample T-test

t test result of average salary comparison 2 levels of minority status shows that t=3.915, P=0.000 which is <0 .05 level. minority status is significantly affect salary.

1.2d Salary and sex - Independent Sample T-test

t test result of average salary comparison gender shows that t=10.945, P=0.000 which is <0 .05 level. gender is significantly affect salary.

1.2e Salary and Formal education – Correlation

Correlation between Salary and formal education is 0.661, P=0.000 which is < 0.05 level. Correlation is significant.

Characteristics are associated with salary are position, minority status, sex and Formal education.

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