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A researcher wanted to examine whether type of dog food (freeze dried meat vs generic brand kibble) would affect dogs' attention span. The researcher hypothesized that dogs who ate freeze dried meat would not have the same attention span as those who ate generic kibble. The researcher used a single sample of 13 dogs, that took part in both treatment conditions. The mean was 7.0 and the SS for the difference in attention spans was 144. Alpha was set at the 0.05 level.  Calculate the appropriate

A researcher wanted to examine whether type of dog food (freeze dried meat vs generic brand kibble) would affect dogs' attention span. The researcher hypothesized that dogs who ate freeze dried meat would not have the same attention span as those who ate generic kibble. The researcher used a single sample of 13 dogs, that took part in both treatment conditions. The mean was 7.0 and the SS for the difference in attention spans was 144. Alpha was set at the 0.05 level.  Calculate the appropriate

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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A researcher wanted to examine whether type of dog food (freeze dried meat vs generic brand kibble) would affect dogs' attention span. The researcher hypothesized that dogs who ate freeze dried meat would not have the same attention span as those who ate generic kibble. The researcher used a single sample of 13 dogs, that took part in both treatment conditions. The mean was 7.0 and the SS for the difference in attention spans was 144. Alpha was set at the 0.05 level.

 Calculate the appropriate t to the nearest thousandths and include the +/- value in front of the t. For example, -5.369.

 What is the corresponding critical t?

 What decision can you make about the null hypothesis?

 Was there a treatment effect?

This image displays a t-Distribution table, commonly used in statistics to determine the critical t-value for a given degree of freedom (df) and cumulative probability. The table is structured in a grid format, with columns representing different t-values (t₀.₅₀, t₀.₂₅, etc.) and rows displaying the degrees of freedom, ranging from 2 to 1000. ### Table Headers: - The table headers indicate cumulative probabilities for both one-tail and two-tail tests. Probabilities range from 0.50 to 0.0005 for one-tailed tests and 1.00 to 0.001 for two-tailed tests. ### Confidence Levels: - A row at the bottom aligns the confidence levels with cumulative probability, ranging from 50% to 99.9%. ### Table Content: - Each cell intersection between a degree of freedom and a cumulative probability column represents a t-value. These are critical values required for hypothesis testing, often used in constructing confidence intervals or conducting t-tests. The table is shaded in alternating rows to enhance readability, helping users quickly locate the required t-value. The degrees of freedom (df) on the leftmost column range from 2 to 1000, with a bottom row for 'z' values, representing the standard normal distribution used in large sample sizes. This table is an essential tool for students and professionals in statistics, allowing them to determine the critical points of the t-distribution for hypothesis testing and other statistical analyses.
Transcribed Image Text:This image displays a t-Distribution table, commonly used in statistics to determine the critical t-value for a given degree of freedom (df) and cumulative probability. The table is structured in a grid format, with columns representing different t-values (t₀.₅₀, t₀.₂₅, etc.) and rows displaying the degrees of freedom, ranging from 2 to 1000. ### Table Headers: - The table headers indicate cumulative probabilities for both one-tail and two-tail tests. Probabilities range from 0.50 to 0.0005 for one-tailed tests and 1.00 to 0.001 for two-tailed tests. ### Confidence Levels: - A row at the bottom aligns the confidence levels with cumulative probability, ranging from 50% to 99.9%. ### Table Content: - Each cell intersection between a degree of freedom and a cumulative probability column represents a t-value. These are critical values required for hypothesis testing, often used in constructing confidence intervals or conducting t-tests. The table is shaded in alternating rows to enhance readability, helping users quickly locate the required t-value. The degrees of freedom (df) on the leftmost column range from 2 to 1000, with a bottom row for 'z' values, representing the standard normal distribution used in large sample sizes. This table is an essential tool for students and professionals in statistics, allowing them to determine the critical points of the t-distribution for hypothesis testing and other statistical analyses.
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