t Tests

Download and save the Week 6: t Tests [DOCX] document.
Complete the assignment within the Word document, and submit it to your instructor by Sunday, 11:59 p.m. central time.

Competencies Measured

By successfully completing this assignment, you will demonstrate
your proficiency in the following course competencies and scoring guide
criteria:

Competency 1: Apply appropriate notation, terminology, procedures, and concepts to statistics problems.

Calculate a one-sample t test in SPSS.
Calculate an independent sample t test in SPSS.
Calculate an independent sample t test in Excel.
Competency 2: Form logical conclusions about real-world problems through descriptive and inferential statistical procedures.

Identify IV, DV, and hypotheses and evaluate the null hypothesis for an independent samples t test.
Determine a statistical test based on type of data, the sample, and purpose.
Competency 3: Evaluate confidence and significance of statistical data.

Calculate confidence intervals using SPSS.

submit your assignment

Prepare: Decide Your Statistical Test

The next step in preparing for your research report is determining
which statistical test to use to analyze your data. You have one sample
(though possibly with multiple measures), and your purpose is to find a
relationship. The following resources can help you.

View Matching Statistical Tests to Hypotheses to practice your knowledge of various tests and their hypotheses.
Dr. Mic’s Maths and Stats. (2012). Choosing which statistical test to use – Statistics help [Video]. Retrieved from https://www.youtube.com/watch?v=rulIUAN0U3w

This video can help you decide as it walks through questions
you can ask and offers several examples. Before you watch, it’s helpful
to know whether your data is nominal, ordinal, or interval/ration.
View Measurement Scales Activity to practice matching the correct units of measurement with various examples.
View Two-Sample Designs to practice your knowledge of the different types of measures and samples.
View Statistical Tests to help you differentiate between a one-sample test, two-sample test, and a test with more than two samples.

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