Analyzing Data: Comparing Means
docsity.com
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Guidelines and tips
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Community
Ask the community
Ask the community for help and clear up your study doubts
University Rankings
Discover the best universities in your country according to Docsity users
Free resources
Our save-the-student-ebooks!
Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors
Statistical Analysis of Means: t-test and ANOVA, Slides of Research Methodology
An overview of various statistical tests used to compare means, including t-test and analysis of variance (anova). It covers different types of t-tests such as 2-sample t, paired t, and 1-sample t, and explains their applications. Additionally, it discusses anova and its extensions, one-way anova and two-way anova. The document also emphasizes the importance of testing for equal variances and choosing the appropriate statistical test based on research objectives.
Typology: Slides
2012/2013
1 / 10
This page cannot be seen from the preview
Don't miss anything!
Related documents
Partial preview of the text
Download Statistical Analysis of Means: t-test and ANOVA and more Slides Research Methodology in PDF only on Docsity!
Analyzing Data: Comparing Means
Are there differences?
• One of the fundament questions of survey
research is if there is a difference among
respondents
• When seeking to evaluate differences in
means, we can use t-test or ANOVA = analysis
of variance
Equal Variances?
- Many statistical procedures assume that although different
samples may come from populations with different means, they have the same variance.
- We can test for this –
- use Bartlett's and Levene's tests.
- Select: Stat > ANOVA > Test for Equal Variances
t-test
- Paired t performs a hypothesis test of the difference
between two population means when observations are
paired (matched).
- When data are paired, as with before-and-after
measurements, the paired t-procedure results in a
smaller variance and greater power of detecting
differences than the 2-sample t.
- Select: Stat > Basic Statistics > Paired t
ANOVA – Analysis of Variance
- ANOVA is similar to regression in that it is used to investigate and model the relationship between a dependent (response) variable and one or more independent (explanatory) variables.
- It is different
- the independent variables are qualitative (categorical)
- no assumption is made about the nature of the relationship
- ANOVA really extends the two-sample t-test for testing the equality of two population means to a more general null hypothesis of comparing the equality of more than two means, versus them not all being equal.
One-way ANOVA
- Select: Stat > ANOVA > One-way
- Performs an one-way ANOVA, with the dependent variable in one column, subscripts in another.
- Select: Stat > ANOVA > One-Way (Unstacked)
- Performs a one-way ANOVA, with each group entered in its own column - Response: Select the column containing the response - Factor: Select the column containing the factor levels