A hypothesis is a prediction about a population. If the probability of the sample results occur by chance is low, then the hypothesis is supported; however, if the chances are high, the hypothesis is not supported.
The steps of hypothesis testing are to define the null and research hypothesis, determine the characteristics of the comparison distribution, establish a Z-cutoff score, calculate Z-scores, plot calculated Z-scores on the comparison distributions, and draw conclusions about the hypothesis.
Lowe defines and distinguishes between one and two-tailed tests. Examples of two- tailed and one- tailed tests are demonstrated.
Significance, in statistics, means the null hypothesis was rejected and the alternative hypothesis was supported. Significance is not due to chance.
For additional digital leasing and purchase options contact a media consultant at 800-257-5126 (press option 3) or email@example.com.
In this video lecture, Professor Naomi Lowe explains hypothesis testing (logic, process, one- and two-tailed tests, and significance in research).
Length: 43 minutes
Copyright date: ©2010
Prices include public performance rights.
Not available to Home Video and Publisher customers.
The Secret to Making Better Decisio...
Prediction by the Numbers
Patterns and Graphs
Gathering and Understanding Data
Statistics With Naomi Lowe- Introdu...
Branches of Statistics: Lecture 1, ...
Summarizing Data: Lecture 1, Part 2
Central Tendency and Variability: L...
Z-Scores: Lecture 3, Part 1
Z-Scores and the Normal Curve: Lect...
132 West 31st Street, 16th Floor
New York, NY 10001
P: 800.322.8755 F: 800.678.3633
Sign Up for Special Offers!
© Films Media Group. All rights reserved.