Use the "attitude data" tab in the exam excel file to answer this question.Imagine you collected data that examined what employees feel when they are overwhelmed withemail. What is email overload's correlation with the following variables? Which correlations arestatistically signi ficant? (Please round to the hundredths place.)Depression -anxiety -cognitive failure -perfectionism -

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Asked Nov 18, 2019
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depression anxiety email overload cognitive failure perfectionism
1.75 1.4 2 2.4 1.6
2.25 2.4 3.75 3 2
2.25 3.8 3.5 2.4 2.2
2.75 3.8 4 3.4 2.4
3.5 2.8 4 2.6 2.6
3 2.4 2.25 2.8 2.6
1 1.4 1.5 2.2 2.8
3 2.8 3 2.4 2.8
2.5 2.2 2.25 3 2.8
2.5 2.4 2.25 3 2.8
3 3.4 3 3.4 2.8
3 3 3 1 3
4 3.4 3.75 2 3
2.25 1 1 2.4 3
3 2.6 3 2.4 3
3 3.6 2.75 3 3
1.75 3 3 3 3
3 3 3 3 3
3.75 3 3 3 3
3.75 3 3 3.4 3
2 1.8 1.5 1.2 3.2
1.5 1 1 1.6 3.2
2.5 1 1 2 3.2
2.5 2 2 2 3.2
2.25 2.2 2 2 3.2
3.5 3.2 3.25 2.6 3.2
2.5 1.4 1 2.8 3.2
3 2.6 2.5 2.8 3.2
1.5 1.4 1 3.6 3.2
1 1 1 1 3.4
2.25 2.8 1.25 1.2 3.4
1 1.6 1.25 1.8 3.4
1.75 2.6 2 1.8 3.4
2 3 2.75 2 3.4
1.25 1 1.75 2.6 3.4
2 2 2 2.6 3.4
2.5 1 1.25 2.8 3.4
1 1 1 3 3.4
3.25 2.6 3.5 3 3.4
2.75 3.2 3.25 3.6 3.4
1.5 1 1 1 3.6
2 1 1 2 3.6
2 1.6 1.5 2 3.6
2.25 3.6 1.5 2 3.6
1.75 1.2 1.25 2.2 3.6
1.75 2 2 2.4 3.6
3.5 1.2 1.25 2.6 3.6
1 2.2 1.75 2.6 3.6
3.25 2 2.75 2.6 3.6
1.75 2 2 2.8 3.6
2.25 2.4 2.25 2.8 3.6
3.25 3.8 2.5 2.8 3.6
2.75 2.8 2.75 3 3.6
2.25 1.2 2 4 3.6
3.75 3.6 3.25 4 3.6
2 1 1 1 3.8
2 1 1 1 3.8
1 1 1 1.8 3.8
2 1 1 1.8 3.8
2 1 1 2 3.8
2.75 1 1.25 2 3.8
1.75 2 1.75 2 3.8
2 2 2 2 3.8
2 1 1 2.2 3.8
2.75 1 1 2.4 3.8
2 2 1.75 2.4 3.8
2.5 2.2 2.5 2.4 3.8
1.5 2.6 2.5 2.4 3.8
1 3 3 2.4 3.8
2.25 3 1.25 2.6 3.8
2.25 1.4 1.25 2.8 3.8
3 1.2 1.75 2.8 3.8
3.25 1.6 2 2.8 3.8
2 2.4 2 2.8 3.8
1.75 2.8 2.25 2.8 3.8
3 1.8 1 3 3.8
3 2 2 3 3.8
4.5 2.2 2.25 3.8 3.8
1 1 1 1 4
1 1 1 1 4
1 1 1 1 4
2 1 1 1 4
2 1 1 1 4
2 1 1 1 4
3.5 1 1 1 4
1.75 1.6 1 1 4
2 2 2 1 4
1.25 1 1 1.2 4
2 1.4 1 1.2 4
2 1 1.5 1.4 4
1 1 1 1.6 4
1 1 1 1.6 4
1.75 1 1 1.6 4
1.75 1 1 1.6 4
2 1 1 1.6 4
4 2 1 1.6 4
1 1 1.25 1.6 4
1 1 1.25 1.6 4
2.5 1.2 1.25 1.6 4
1 1.4 1.25 1.6 4
2 1 1 1.8 4
1.5 1.2 1.75 1.8 4
1 1 1 2 4
2 1 1 2 4
1.25 2.4 1 2 4
2.25 1 1.25 2 4
1 1.4 1.25 2 4
2.5 2 1.5 2 4
3.5 1.4 1.75 2 4
1.75 1 1 2.2 4
2 1 1 2.2 4
2 1 1 2.2 4
2 1 1 2.2 4
3 1 1 2.2 4
3.25 1 1 2.2 4
1 1.4 1.25 2.2 4
3.75 1 1.5 2.2 4
1.5 1.4 1.75 2.2 4
2 2 2 2.2 4
2 2 2 2.2 4
2.75 2.2 2.25 2.2 4
3 1 1 2.4 4
3 1.2 1 2.4 4
1.5 1.4 1.25 2.4 4
2.25 3.6 1.25 2.4 4
3 2 1.5 2.4 4
2.25 1.8 2 2.4 4
3.5 1 1.25 2.6 4
2 1 1.5 2.6 4
3.25 2 2 2.6 4
3.5 1.8 2.25 2.6 4
3.25 2.4 4 2.6 4
2 1.4 1.5 2.8 4
3.5 2.8 1.5 2.8 4
3.25 2.2 2 2.8 4
1 2 2 3.4 4
2.25 5 5 3.4 4
3.5 2.2 2.75 3.6 4
1 1 1 1 4.2
1.25 1 1 1 4.2
1.25 1 1 1.4 4.2
2.25 1 1 1.4 4.2
2 1.2 1.25 1.4 4.2
2 1.4 1 1.8 4.2
2 1.4 1.5 1.8 4.2
1.5 1 1 2 4.2
2 2 1.75 2 4.2
2.25 1.8 1.5 2.2 4.2
3.75 1.2 1.75 2.2 4.2
1.75 2.2 2 2.2 4.2
2.5 2.2 2 2.2 4.2
2 1 1 2.4 4.2
2.25 1.2 1.25 2.4 4.2
2.75 1.4 1.75 3 4.2
1.5 2.4 2 3.2 4.2
2 1 1 2 4.4
3.25 1.4 1.5 2 4.4
2.25 1.6 2 2.2 4.4
1.5 2.2 2.25 2.2 4.4
1.5 3.4 2.5 2.2 4.4
1.75 1 1 2.4 4.4
3.5 1.8 2.5 2.4 4.4
2.25 2 1.25 2.6 4.4
1.75 1 1.75 2.8 4.4
3 1.4 2.25 2.8 4.4
2.5 2.6 2.25 4 4.4
1 1 1 1 4.6
1.5 1 1.25 1.4 4.6
1 1.2 1 1.6 4.6
2 1.4 1.5 1.8 4.6
1 1.4 1.5 2 4.6
2 1.8 2.25 2 4.6
3.75 1 1 2.8 4.6
3 2.2 1.5 2.8 4.6
2.5 2.6 2.5 2.8 4.6
2.25 1.2 1.75 3 4.6
2.5 1 1 3.4 4.6
1 1 1 1 4.8
1 1 1 1 4.8
3 2 1.75 1 4.8
1 1 1 1.2 4.8
1 1 1.5 1.2 4.8
1.5 1.6 1.25 1.6 4.8
3.25 1 1 1.8 4.8
1.5 1 1.25 2 4.8
2.5 1 1.5 2 4.8
2 1.2 1.75 2 4.8
1 2.2 2.5 2 4.8
1.25 1 1.5 2.2 4.8
1.5 1 1.5 2.2 4.8
3.75 2.8 3.25 2.2 4.8
2.75 1.6 1.5 2.4 4.8
1 1 2 2.4 4.8
1.75 2 2 2.4 4.8
2 1 1 2.6 4.8
2 1 1 2.6 4.8
2.25 2.4 1.5 2.6 4.8
3 1.2 2 2.6 4.8
1.75 1.2 1.5 3 4.8
4.5 2.4 2 3.6 4.8
1 1 1 1 5
1 1 1 1 5
1 1 1 1 5
1 1 1 1 5
1 1 1 1 5
1 1 1 1 5
1 1 1 1 5
1 1.2 1 1 5
1.25 1.4 1 1 5
1 1.2 1.25 1 5
1.5 1 1.75 1 5
1 1 1 1.2 5
1.25 1 1 1.2 5
1 1.8 1.5 1.2 5
1 1 1 1.4 5
1.75 1 1 1.4 5
1 1.4 1 1.4 5
2 1 1.25 1.4 5
2.5 1 1.25 1.4 5
1 1 2.25 1.4 5
2.5 1 1.25 1.6 5
2 1.2 1.25 1.6 5
2 2.2 3.25 1.6 5
1 1 1 1.8 5
2.5 1 1 1.8 5
1 1 1.5 1.8 5
1 2 1.5 1.8 5
1 1 1 2 5
1.75 1 1 2 5
2 1 1 2 5
2 2 2.25 2 5
1.5 1 1 2.2 5
3.75 1.6 1.75 2.2 5
2.5 1.2 1.5 2.4 5
3 1.8 2 2.4 5
2 2 2 2.4 5
2 1 1.5 2.6 5
4 3 2.5 2.8 5
4 4.6 4.5 2.8 5
1.25 1 1 3 5
2.5 2 2 3 5
2 2.2 2 3 5
4 3.8 2.25 3 5
2.5 1.2 1.75 3.4 5
Use the "attitude data" tab in the exam excel file to answer this question.
Imagine you collected data that examined what employees feel when they are overwhelmed with
email. What is email overload's correlation with the following variables? Which correlations are
statistically signi ficant? (Please round to the hundredths place.)
Depression -
anxiety -
cognitive failure -
perfectionism -
help_outline

Image Transcriptionclose

Use the "attitude data" tab in the exam excel file to answer this question. Imagine you collected data that examined what employees feel when they are overwhelmed with email. What is email overload's correlation with the following variables? Which correlations are statistically signi ficant? (Please round to the hundredths place.) Depression - anxiety - cognitive failure - perfectionism -

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Expert Answer

Step 1

Correlation calculation:

We have solved part of this problem using Excel.

Enter the 5 columns of the data in columns A, B, C, D, and E in Excel.

Go to Data > Data Analysis > Correlation > OK.

Enter Input Range as $A$1:$E$245.

Tick on Labels in first row.

Click OK.

The obtained correlation matrix is displayed below:

cognitive failure perfectionism email overload
depression
anxiety
depression
0.435934732
anxiety
1
cognitive failure 0.511233419
0.484139878
perfectionism
-0.238302078 -0.372388426
0.304886295
1
email overload
0.454779893
0.81483527
0.514786787 -0.361143401
help_outline

Image Transcriptionclose

cognitive failure perfectionism email overload depression anxiety depression 0.435934732 anxiety 1 cognitive failure 0.511233419 0.484139878 perfectionism -0.238302078 -0.372388426 0.304886295 1 email overload 0.454779893 0.81483527 0.514786787 -0.361143401

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Step 2

Correlation values:

The last row of the above output shows the correlation coefficients of “email overload” with depression, anxiety, cognitive failure, and perfectionism.

Thus, the correlations of email overload with the variables are:

Depression- 0.45;

Anxiety- 0.81;

Cognitive failure- 0.51;

Perfectionism- –0.36.

Step 3

Test for correlation:

Suppose ρ is the true population correlation coefficient between two variables, and r is the observed sample correlation coefficient.

In order to test whether there is statistically significant correlation between the two variables, based on the sample observations, the null and alternative hypotheses are:

H0: ρ = 0, vs. H1: ρ ≠ 0.

The test statistic for the test is:

t = [r √ (n – 2)] / √...

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