In the Minitab worksheet attached to this assignment, you'll find data on the stopping distances of 4 different tire brands Using Minitab Perform a One Way ANOVA to see if there is a difference in the average stopping distances of these 4 tire brands Make sure you have Minitab do the Fisher comparisons Comparisons button in Minitab when performing the ANOVA test Paste MTB Output Here Make sure it includes the Fisher (LSD) comparisons Do not worry about all 7 steps, but using Minitab output (F stat and p value) , is there a significant difference in the stopping distance of at least one of the four tires Make sure you tell me how you come to your conclusion Interpret discuss the results of Minitab's Fisher (LSD) comparisons (see output) What do you recommend to tire buyers Note that a longer stopping distance is a BAD thing for a tire Also in the posted Minitab worksheet you'll find data on daily bagel sales at 3 different locations (Athens, Huntsville, and Decatur) of a local bagel business Again, using Minitab First, have Minitab display descriptive statistics (under the Basic Statistics tab) for Athens, Huntsville, and Decatur locations Paste MTB Output Here Randomized Block ANOVA (General Linear Model) with location AND day both included as factors Paste MTB Output Here Using the Minitab output, perform a hypothesis test to determine whether there is a significant difference in revenue by Location Do not worry about all 7 steps, but tell me how you reach your conclusion (using F stat and p value for Location) Although Location is the primary focus, also perform a hypothesis test to determine if the blocking variable (Day) was significant as well In general terms, what sort of changes would you have seen in the results of your test on Location if we had left out the blocking variable (Day) Again, I am not asking for an exact, numeric answer I simply want to know what general changes would have occurred While strict multiple comparison tests (e g , LSD) are not possible for this model, what general conclusions can you come to about sales at the 3 locations (Look back at your descriptive statistics from part a ) Nothing to paste answer here Sales Location Day Tire A Tire B Tire C Tire D 140 Athens Mon 150 153 155 150 181 Athens Tues 152 150 150 164 127 Athens Wed 151 156 157 159 172 Athens Thur 149 151 158 162 161 Athens Fri 153 155 155 180 102 Athens Sat 123 Athens Sun 178 Huntsville Mon 215 Huntsville Tues 115 Huntsville Wed 182 Huntsville Thur 185 Huntsville Fri 121 Huntsville Sat 167 Huntsville Sun 197 Decatur Mon 123 Decatur Tues 110 Decatur Wed 119 Decatur Thur 157 Decatur Fri 95 Decatur Sat 80 Decatur Sun

The Answer is in the image, click to view ...

Answered step by step

Verified Expert Solution

Link Copied!

Question

1 Approved Answer

Posted on May 19, 2024

In the Minitab worksheet attached to this assignment, you'll find data on the stopping distances of 4 different tire brands. Using Minitab : Perform a

In the Minitab worksheet attached to this assignment, you'll find data on the stopping distances of 4 different tire brands. Using Minitab:
1. Perform a One-Way ANOVA to see if there is a difference in the average stopping distances of these 4 tire brands. Make sure you have Minitab do the Fisher comparisons [Comparisons button in Minitab] when performing the ANOVA test.

[Paste MTB Output Here. Make sure it includes the Fisher (LSD) comparisons.]

Do not worry about all 7 steps, but using Minitab output (F-stat and p-value), is there a significant difference in the stopping distance of at least one of the four tires? [Make sure you tell me how you come to your conclusion.]

Interpret/discuss the results of Minitab's Fisher (LSD) comparisons (see output). What do you recommend to tire buyers? Note that a longer stopping distance is a BAD thing for a tire.

Also in the posted Minitab worksheet you'll find data on daily bagel sales at 3 different locations (Athens, Huntsville, and Decatur) of a local bagel business. Again, using Minitab:
1. First, have Minitab display descriptive statistics (under the Basic Statistics tab) for Athens, Huntsville, and Decatur locations.

[Paste MTB Output Here]

Randomized Block ANOVA (General Linear Model) with location AND day both included as factors.

[Paste MTB Output Here]

Using the Minitab output, perform a hypothesis test to determine whether there is a significant difference in revenue by Location. Do not worry about all 7 steps, but tell me how you reach your conclusion (using F-stat and p-value for Location).
Although Location is the primary focus, also perform a hypothesis test to determine if the blocking variable (Day) was significant as well.
In general terms, what sort of changes would you have seen in the results of your test on Location if we had left out the blocking variable (Day). Again, I am not asking for an exact, numeric answer; I simply want to know what general changes would have occurred.
1. While strict multiple comparison tests (e.g., LSD) are not possible for this model, what general conclusions can you come to about sales at the 3 locations? (Look back at your descriptive statistics from part a.)

[Nothing to paste. answer here.]

Sales Location Day Tire A Tire B Tire C Tire D

140 Athens Mon 150 153 155 150 181 Athens Tues 152 150 150 164 127 Athens Wed 151 156 157 159 172 Athens Thur 149 151 158 162 161 Athens Fri 153 155 155 180 102 Athens Sat 123 Athens Sun 178 Huntsville Mon 215 Huntsville Tues 115 Huntsville Wed 182 Huntsville Thur 185 Huntsville Fri 121 Huntsville Sat 167 Huntsville Sun 197 Decatur Mon 123 Decatur Tues 110 Decatur Wed 119 Decatur Thur 157 Decatur Fri 95 Decatur Sat 80 Decatur Sun