1.
Statistics
Md Muktadir Islam
ID: 2223031014
Analyzing Dataset using SPSS
Presented to
Syed Shahadat Hossain, Ph.D
Professor, ISRT, DU
Presented by
Md Muktadir Islam
ID: 2223031014

2.
Variable Selection for Analysis Sample 9

3.
Sample 9
Data View
Number of
Individual data: 57

4.
Educational Level Skewness: .040/.316 = 0.126 (between -1.96 to +1.96)
Kurtosis: .066/.623 = 0.106 (between -1.96 to +1.96)

5.
Lowest Education level 8 years
25% of the employee have 12 years of
Education
75% of the employee have 16 years
Education
Highest Education Level 21 years
Stem and leaf display of Education Level Box plot of Education Level
Right skewed

6.
Beginning Salary
Skewness:
1.939/.316 = 6.136 (not between -1.96 to +1.96)
Kurtosis:
3.764/.623 = 6.041 (not between -1.96 to +1.96)

7.
Mode 12

8.
25% of the Employee get $ 12,450
as their Beginning Salary
75% of the Employee get $ 18,750
as their Beginning Salary
Box plot of Beginning Salary
Stem and leaf display of Beginning
Salary
left skewed
7 outliers

9.
Correlation Analysis
 Education Level
 Beginning Salary

10.
Independent Variable : Education Level
Dependent Variable : Beginning Salary
R Square= 43% , So 43% of the variability of Beginning Salary can be
explained through educational level
Coefficients of Determiner

11.
Linear Relationship in Graphs

12.
Regression Analysis
If the educational level increased by 1 year the beginning salary will be increased by
1757.943 dollars.
The educational level significantly influences the beginning salary

13.
Let,
Ho: µ=21,000, Ha: µ < 21,000
Since the significance value is less than 0.05 , so it
can be said that there is enough evidence to reject
null hypothesis.
HypothesisTesting of Beginning Salary

14.
Hypothesis Testing of Educational Level
Let,
Ho: µ=16, Ha: µ ≠16
Since the significance value is less than 0.05 , so it can be said that there
is enough evidence to reject null hypothesis.

15.
Thank You