Do one correlation between two independent variables such as age and education.

Question

Do one correlation between two independent variables such as age and education. Do the second correlation on an independent variable (such as age) and the dependent variable (such as score). Remember that most people never see the actual output or data; they read the results statements by the researcher, so your summary must be accurate.

Calculate the Pearson product-moment correlations between at least 2 sets of variables in your data set. Do one correlation between two independent variables such as age and education. Do the second correlation on an independent variable (such as age) and the dependent variable (such as score).

Summarize the results of the calculation in 50 to 90 words.

Explanation / Answer

Correlation = Correlation shows the relation between two variables

The range of Correlation is -1 to 1

If value of Correlation is 0 then there is no relation between two variable.

If Correlation value greater than 0 means the positive correlation between two variable means if the value of the first variable increases then second also increases.

If Correlation value less than 0 means the negative correlation between two variable means if a value of the first variable decreases then second also increases.

Correlation between Age and score,

> Age
[1] 23 23 24 22 21 23 24 23 20 23
> Score
[1] 41 73 58 54 79 88 48 84 43 42
> cor(Age,Score)
[1] 0.04302961

Age and Score not depend on each other

Correlation between Age and Education(in class 15th,16th,17th students)

> Age
[1] 23 23 24 22 21 23 24 23 20 23
> Education_Class
[1] 16 16 17 16 15 17 17 16 15 16
> cor(Age,Education_Class)
[1] 0.8809524

It is strongest correlation that means if Age icreases then education also high.

but it's not true because correlation only shows the relation between continuous variable and education is not the continuous variable it is categorical variable we want to use the chi-square test to show the relationship between categorical variable.

Pearson Correlation Test:

Between Age and Score

Pearson's product-moment correlation

data: Age and Score

t = 0.12182, df = 8, p-value = 0.906

alternative hypothesis: true correlation is not equal to 0

Correlation = 0.04303

P-value > 0.05 means we accept null hypothesis i.e. no correlation between age and score

Between Age and Education:

data: Age and Education_Class

t = 5.2656, df = 8, p-value = 0.0007593

alternative hypothesis: true correlation is not equal to 0

Correlation = 0.88096

P-value < 0.05 we reject the null hypothesis i.e. age depend on education

>>>>>>>>>>>> Best Luck >>>>>>>>>>>>

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