600 words - 3 pages

Unit 4 – Hypothesis Testing & Variance

Abstract

There are two tests that are preformed following a two-tailed hypothesis test, using a .05 significance level. The first test is intrinsic by gender and the second is extrinsic variable by position type.

This section will be taking a closer look at intrinsic satisfaction by gender and extrinsic satisfaction by position. Separate hypothesis test will be performed on both variances with the outcomes.

Hypothesis Test #1 Looking at Intrinsic Satisfaction by Gender

H0:Males= μ Females

H1:Males= μ Females

∝ = .05

Significance level: 0.05

T statistic: 2.05

Critical T values: -1.98 and 1.98

P value: 0.04

Since the test statistics of 2.05 is greater than critical value of 1.98 we reject to reject the Ho.

The decision made for the intrinsic job satisfaction survey, which intrinsic ...view middle of the document...

Hypothesis Test #2 Looking at Extrinsic Satisfaction by Position

H0:Hourly= μ Salary

H1:Hourly= μ Salary

∝ = .05

Significance level: 0.05

T statistic: -0.84

Critical T values: -1.98 and 1.98

P value: 0.41

Since the test statistics of -0.84 is less than the critical value of 1.98 we fail to reject the Ho.

The data supports Ho the fact that the outcome is different when comparing males to females.

There are 137 employees that are hourly and 53 that are salary employees that means that 84 more employees are hourly, but in comparing to the extrinsic survey which is when an employee are motivated to perform a task in order to earn a reward or avoid a punishment. The results show that outcome is the same whether it is salary or hourly.

Z and T Tests

“The difference between the z-test and the t-test is in the assumption of the standard deviation σ of the underlying normal distribution. A z-test assumes that σ is known; a t-test does not. As a result, a t-test must compute an estimate s of the standard deviation from the sample (MathWorks, 2013).”

Samples and Populations

A population includes each element from the set of observations that can be made. Samples consist only of observations drawn from the population. Samples are randomly chosen from a population but there are items to take into consideration. When the sample size is of adequate size and without specific methods the mean of all the samples will equal the mean of the population. The larger the size of the sample that has been selected from the population the smaller the standard deviation of the sampling distribution of means.

In conclusion is important to know that hypothesis testing is used to find conclusions about populations by examining a sample of that population. The purpose of Hypothesis testing is to provide information to management or pupils in helping them make decisions right for their company or decisions.

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