Week 2 - Assignment: Apply the T-Test Reflect in e Portfolio Submit Feedback

BUS-7106-2

NORTHCENTRAL UNIVERSITY ASSIGNMENT COVER SHEET

Student Date: 11/10/2019

Course ID # BUS-7106 V1 Professor:

Assignment Title: Apply the T-Test Assignment Number: 2

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Introduction

In this study, I analysis the null hypothesis and apply the T-Test for the dataset in a company

between two groups of employees. By figuring out the mean, the average of all data samples will

be calculated and it looks like the average in field Two is higher than the average in field one.

However, it will be the only part of the subject which the mean will show us since we might have

various distributions based on those distributions and the samples’ variance, there might be an

obvious difference among them and the t- value would be the solution. In order to find the

differences between the two samples, company should calculate the ratio of samples by finding the

difference between the absolute values and the means. Since the standard deviation showing us

how the data spreading from the mean, I am not only calculating the standard deviation, but also, I

will square SD in order to show the variance.

If the variance gets increased, the value will be decreased. I have increased the sample’

numbers basically, would increase the data and will give us the higher number of t-value (Hughes,

L. W., & Palmer, D.K. 2007).

I test the null hypothesis to show statistically that there is not significantly difference among

the data which is considered as critical value since, the t-value result would be less than that.

However, I won’t reject the null hypothesis, and if the t-value is more than the critical value, the

null hypothesis would be rejected. By considering the alternate Hypothesis, there might be a kind

of situation among the two datasets.

As we know we have

sd 1 2

n 1

√(¿ + sd 2

2

n 2 )

t −value= mean 2−mean 1

¿

. Based on that, I calculate the results.

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Hypothesis:

Null hypothesis: H0:

Alternative hypothesis: H1:

Using SPSS software hypothesis testing is:

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BUS-7106-2

here significance value is 0.449>0.05 Then I accept the H0 so there is no statistically significant

different among both groups.

Using MS excel:

F-Test Two-Sample for Variances

Variable 1 Variable 2

Mean 3.675 3.758333

Variance 0.694612 0.657256

Observations 30 30

df 29 29

F 1.056837

P(F<=f) one-tail 0.441345

F Critical one-tail 1.860811

here also 0.441345>0.05 so we accept H0 so there is no difference

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BUS-7106-2

conclusion:

Here we accept H0 so both groups have not any differences and they have equal means.

About independent t-test:

1) The two-sample t-test is utilized for comparing the two means of two independent populations

denoted by

2) samples of n1 and n2 observations are randomly selected from the two populations

3) The greater the difference between sample means the greater the evidence against the hypothesis

of equality of populations means are untrue.

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References

Hughes, L. W., & Palmer, D.K. (2007). An investigation of the effects of psychological contract

and organization-based self-esteem on organizational commitment in a sample of permanent

workers.

https://eds-a-ebscohost-com.proxy1.ncu.edu/eds/detail/detail?vid=0&sid=eab533f1-4943-42e6-

9ff2-999ee4065f0b%40sdc-v-sessmgr01&bdata=JnNpdGU9ZWRzLWxpdmU%3d#AN=2009-

08811-005&db=psyh

Field, A. (Academic). (2012). T-Test. SAGE Research Methods.

Steckler, A., & McLeroy, K. R. (2008). The importance of external validity.

American Journal of Public Health

Gepp, A., Kumar, K. (2012). Business failure prediction using statistical techniques: A review.

In Kumar, K., & Chaturvedi, A. (Eds.). Some Recent Developments in Statistical Theory and

Applications.

Sommer, B. (n.d.). Reliability and validity. UC Davis. Retrieved from

ht t p: / /psc.dss.u c d a vis.edu/so m me r b/so m me r d e mo / in t ro/v a l i di t y .htm

The Association for Educational Communications and Technology (2001). What is descriptive

research. Retrieved from ht t p: / /ww w . aec t.o r g /edt e c h/ed1/41/4 1 - 01.ht m l

Maheshwari, T., Reganti, A. N., Gupta, S., Jamatia, A., Kumar, U., Gamback, B., & Das, A.

(2017). A societal sentiment analysis: Predicting the values and ethics of individuals by

analyzing social media content. Proceedings of the 15th Conference of the European

Chapter of the Association for Computational Linguistics

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