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Difference in Miles Ran between the two halves of the data

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Consider the attached data on Miles Ran. Divide your data in half, your first 8 observations and your last 7 observations. Use ANOVA to test to see if there is a significant difference between the two halves of your data.

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Null Hypothesis (Ho): There is no significant difference in the population Miles Ran between the two halves of the data.
Alternative Hypothesis (Ha): There is a significant difference in the ...

Solution Summary

This solution is comprised of a detailed explanation for Analysis of variance and least square regression. A data is divided in such a way so that the ANOVA can be performed on the given data. Full description is given including, Null and Alternative Hypotheses, level of significance, ANOVA table, P-value, F-value, decision about rejecting or not rejecting the null hypothesis along with concluding remarks are given in the solution. ANOVA output is generated using excel add ins "Data Analysis".

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Created a realistic value and indicated the scale of measurement for the given attributes.

Assignment 3: Scales of Measurement
For each measure or attribute in the following list, create a realistic example (for example, weight = 150 pounds) and indicate the scale of measurement (nominal, ordinal, interval, or ratio). Please note the example given is usually called a value, and the term "value" is used in a generic sense; the answer does not have to be a number; some of the answers might be words:
Attribute Example Scale
The amount of time it takes you to run a mile
Gender
The number of times a dog barks before eating
The order in which first-grade kids learn to read
The number of cell phone numbers in an address book

After deciding on the scale of measurement for the above attributes, change all the examples or values so they will fit into a different scale of measurement. For example, weight can be made into an ordinal scale of measurement by calling it weight group and a realistic measurement would be thin. Then, state what scale this new measurement would fit into. The most challenging one is gender. Can this scale be altered? Why?
Last, but not the least, explain why many scientists believe most data labeled as ratio are really interval data.

Cite any sources you use using APA format on a separate page

Created a realistic value and indicated the scale of measurement for the given attributes.

Changed the current scale of measurement to fit into a different scale of measurement and explained what scale the new measurement would fit into.

Analyzed and justified whether the scale for measuring gender can be altered.

Analyzed and explained why many scientists believe most data labeled as ratio data are really interval data.

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