SPSS Report
QMS 202 – SPSS Term Project Winter 2012
Submitted: March 29th 2012
Dr. Changping Wang
QMS 202 – SPSS Project
Part A – Mean Prices between Residential Properties in Toronto, San Francisco and Montreal
Introduction
The data for the first test to be conducted by our group consists of the prices of residential properties in various locations. The locations are Toronto, San Francisco and Montreal. The values of the samples are all represented in Canadian Dollars. The data taken are based on the residential property prices on January 8th 2012. Our group will execute a test to determine if there is a significant difference in the mean residential property prices for Toronto, San Francisco and Montreal. Furthermore, if the tests conclude that there is a difference in mean prices, our group will indicate where the prices are higher or lower.
Hypothesis Testing
For this data set, our group has chosen to conduct a one way Analysis of Variance F test (one-way ANOVA F-test). A one-way ANOVA F-test is appropriate in this example since it is a hypothesis technique that is used to compare means from three or more populations. Since the data set reflects the mean prices of residential properties in Toronto, San Francisco and Montreal, a one way ANOVA F-test is sufficient.
By having at least three samples in the data, our group has eliminated the idea of testing the claim by using different tests, such as a “two sample T-test”, a “paired sample T-test” or a “two sample Z test.”
In order for a one way Analysis of Variance F test to be conducted, the following conditions must be met:
(1) Each sample must be selected from a normal, or approximately normal, population.
(2) The samples must be independent and randomly selected.
(3) Each population must have the same variance.
Looking at the conditions stated above, all the samples provided by the Toronto Real Estate Board reflect data from that are randomly selected, which are independent of each other. That is,
Submitted: March 29th 2012
Dr. Changping Wang
QMS 202 – SPSS Project
Part A – Mean Prices between Residential Properties in Toronto, San Francisco and Montreal
Introduction
The data for the first test to be conducted by our group consists of the prices of residential properties in various locations. The locations are Toronto, San Francisco and Montreal. The values of the samples are all represented in Canadian Dollars. The data taken are based on the residential property prices on January 8th 2012. Our group will execute a test to determine if there is a significant difference in the mean residential property prices for Toronto, San Francisco and Montreal. Furthermore, if the tests conclude that there is a difference in mean prices, our group will indicate where the prices are higher or lower.
Hypothesis Testing
For this data set, our group has chosen to conduct a one way Analysis of Variance F test (one-way ANOVA F-test). A one-way ANOVA F-test is appropriate in this example since it is a hypothesis technique that is used to compare means from three or more populations. Since the data set reflects the mean prices of residential properties in Toronto, San Francisco and Montreal, a one way ANOVA F-test is sufficient.
By having at least three samples in the data, our group has eliminated the idea of testing the claim by using different tests, such as a “two sample T-test”, a “paired sample T-test” or a “two sample Z test.”
In order for a one way Analysis of Variance F test to be conducted, the following conditions must be met:
(1) Each sample must be selected from a normal, or approximately normal, population.
(2) The samples must be independent and randomly selected.
(3) Each population must have the same variance.
Looking at the conditions stated above, all the samples provided by the Toronto Real Estate Board reflect data from that are randomly selected, which are independent of each other. That is,