Week 5 - Assignment: Identify Analysis Tools in Published Research

6/28/22, 4:02 PM BUS-7105 v3: Statistics I (7103872203) - BUS-7105 v3: Statistics I (7103872203)

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Week 5

BUS-7105 v3: Statistics I (7103872203)

Hypothesis Testing: An Introduction to Various Parametric Applications

A variety of statistical tools can be used to investigate a hypothesis. These tools allow us

to compare an average score against a standard (e.g., the z-test).

Other tools allow us to compare the means of two groups. One is the independent

samples t-test that is used to explore mutually exclusive groups (e.g., treatment and control, men and women, etc.) across one dependent variable. You will have the

opportunity to conduct a t-test for the signature assignment.

A paired samples t-test (also called a t-test for related samples) compares two related

samples, or the same samples (subjects) observed at two different time points. A example

of the latter is a comparison of pre-test to post-test scores following an intervention.

Another set of statistics used for hypothesis testing includes analysis of variance (also

known as ANOVA). We use ANOVA to test the statistical significance of differences

among means of three or more groups across one dependent variable. For example, we

may wish to compare work engagement across three different age groups. For example,

we may hypothesize that people under 30 years of age (group 1) are less engaged in their

jobs than those from 31 to 50 years of age (group 2), while those over 50 years of age

(group 3) are the most engaged. ANOVA can be used to examine mean job engagement

scores across these age groups. You will have the opportunity to conduct an ANOVA test

for the signature assignment.

A repeated measures ANOVA is used to examine the evolution of a variable over several

time periods (i.e., longitudinal analysis) or more than two groups and how they differ on a

variable of interest.

Other tests that may be used to examine differences across three or more groups are:

Analysis of Covariance (ANCOVA). This test extends the ANOVA to provide a method

to control for variables extraneous to the test that may influence variance in the

dependent variable. These variables are referred to as covariates.

Multivariate Analysis of Variance (MANOVA). This test extends the ANOVA to

provide a method to include multiple dependent variables that are related.

6/28/22, 4:02 PM BUS-7105 v3: Statistics I (7103872203) - BUS-7105 v3: Statistics I (7103872203)

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Books and Resources for this Week

Cho, H.-C., & Abe, S. (2013). Is two-

tailed testing for directional research

hypotheses tests legitimate? Journal of

Business Research, 66, 1261-1266. Link

NCU School of Business Best Practice

Guide for Quantitative Research Design

and Methods in Dissertations Link

Multivariate Analysis of Covariance (MANCOVA). This test extends the ANCOVA to

examine multiple dependent variables while controlling for one or more covariates.

Each of these are omnibus tests. That is, they provide an overall test to determine

statistically significant difference among three or more groups however, they do not

specify what kind of differences exist among which groups. Post hoc comparisons are

performed to test the statistically significance of differences between group means

computed post (after) having performed the omnibus test. In SPSS, the researcher needs

to request post-hoc testing. Multiple post hoc tests are offered based on the assumption

of (substantially) equal variances (homogeneity of variance).

Last, we will discuss how we can use a tool called linear regression to make predictions

about how one variable may influence another. In Week 6, we will focus solely on the

correlation, which is an element of the regression analysis.

Be sure to review this week's resources carefully. You are expected to apply the

information from these resources when you prepare your assignments.

Reference:

Weiers, R. M. (2011). Introduction to business statistics (7th ed.). Boston, MA: Cengage Learning.

90.91 % 10 of 11 topics complete

6/28/22, 4:02 PM BUS-7105 v3: Statistics I (7103872203) - BUS-7105 v3: Statistics I (7103872203)

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Introduction to Business Statistics (7th

ed.) External Learning Tool

Knapp Ph.D., H. (Academic). (2016).

ANCOVA [Video]. SAGE Research

Methods Video Link

Knapp Ph.D., H. (Academic). (2016).

ANOVA [Streaming Video]. SAGE

Research Methods Video Link

Knapp Ph.D., H. (Academic). (2016).

ANOVA Repeated Measures [Video].

SAGE Research Methods Link

Knapp Ph.D., H. (Academic). (2016).

MANOVA [Video]. SAGE Research

Methods Video Link

Knapp, H. (Academic). (2017). Paired t-

test [Streaming video]. Retrieved from

SAGE Research Methods. Link

Knapp, H. (Academic). (2017). T-test

[Streaming video]. Retrieved from

SAGE Research Methods. Link

Strangman, L., & Knowles, E. (2012).

Improving the development of

student’s research questions and

hypotheses in an introductory business

research... Link

6/28/22, 4:02 PM BUS-7105 v3: Statistics I (7103872203) - BUS-7105 v3: Statistics I (7103872203)

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Week 5 - Assignment: Identify Analysis Tools in

Published Research Assignment

Due July 3 at 11:59 PM

This week you will locate three quantitative studies addressing a topic in your area of

specialization. At minimum, two different statistical tests should be represented.

For example, you might search the literature for studies in transformational leadership and

you may find two that used regression analysis and a third that used a t-test. For each

study:

1. State the null and alternative hypotheses (Hint. The authors will note the

alternative hypotheses, but you will have to infer the null as those aren’t typically

stated in published research)

2. Identify the statistical test used to determine statistical significance (e.g., t-test,

analysis of variance, multiple regression, etc.).

3. Identify the test statistic, note it, and explain what it means (e.g., t=3.47).

4. Identify the significance level used in each study

5. Identify whether or not the authors found support for their

hypotheses. Consider sample size and Type I and Type II error. 6. Explain the implications of each finding.

Identify whether or not the authors found support for their hypotheses.

Consider sample size and Type I and Type II error.

Explain the implications of each finding.

Length: 4 to 6 pages

References: Include a minimum of 3 scholarly resources.

Your paper should demonstrate thoughtful consideration of the ideas and concepts

presented in the course and provide new thoughts and insights relating directly to this

topic. Your response should reflect scholarly writing and current APA standards. Be sure

to adhere to Northcentral University's Academic Integrity Policy.

Upload your document and click the Submit to Dropbox button.

6/28/22, 4:02 PM BUS-7105 v3: Statistics I (7103872203) - BUS-7105 v3: Statistics I (7103872203)

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