Dataset overview
Suppose market research company XYZ shows potential buyers two versions of a laptop and asks them how much they would pay for version 1 and version 2.   Some of the buyers come from region A and some come from region B, for example region A could be Sydney and region B could be outside of Sydney. A dataset showing you the buyers answers is given on moodle
The variables of the data set are:
“Which region? Region A (A) or Region B (B)”
“How much would you pay for version 1?”
“How much would you pay for version 2?”
“Would you pay more for version 1? Yes (y) or No (n)”
The columns “student number” and “which sample” are variables they are used to give every student their own sample
You need to submit discussion of your dataset as a word file,
You also need to submit an excel file that shows you can summarize the dataset without using the automatic dataset summarizer and p-value calculator
Instructions explaining how to discuss the dataset in a word file
a) Use the automatic dataset summarizer to make a summary that lets you investigate the relationship between the variables “Which region?” and “How much would they pay for version 1?”.  Paste the summary into the word file. Briefly comment on the relationship between the variables.
b)  Use the automatic dataset summarizer to make to Make a graph that lets you investigate the relationship between the variables  “How much they would pay for version 1” and “How much would they pay for version 2” and paste it into the word file . Briefly comment on the relationship between the variables.
c) Use the automatic dataset summarizer to make a summary that lets you investigate you investigate the relationship between the variables “Which region?” and “would you pay more for version 1” and paste the summary into the word file. Briefly comment on the relationship between the variables.
d) Find a 95% confidence interval for the variable “would you pay more for version 1”
e) Find the test stat for testing the claim that people would pay more than \$1000 for version 1 on average.
This is the same as finding the zscore for the sample mean if you assume the population mean is 1000 and the population  standard deviation is the same as the sample  standard deviation.
To this question you need to find the sample size, mean and standard deviation of the variable
“how much would you pay for version 1”, This is not difficult you can either use the =count(), =average() and =stdev() command, you would also get the relevant information when you do part (b) of the excel task.
f) Test the claim there is a relationship between the variables “Which region?” and “How much would they pay for version 1?”. Use the automatic dataset summarizer to get the p-value. Interpret the p-value in simple terms. You are not required to discuss H0 and H1.
g) Test the claim there is a relationship between the variables “Which region?” and “Would they pay more for version 1?”. Use the automatic dataset summarizer to get the p-value. Use the automatic dataset summarizer to get the p-value. Interpret the p-value in simple terms you are not required to discuss H0 and H1.
h) Briefly describe some other variables that could be used in a dataset if you wanted to help a business that makes laptops and explain why the variables would be useful. (300 words)
i) Briefly describe what is meant by the phrase “lurking variables” and explain why it is important to consider lurking variables when writing a report (300 words)

j) Briefly describe how you would make a report that uses the information from at least 5 of the previous parts of the assignment, the previous parts of the assignment are parts (a),(b),(c),(d),(e),(f),(g),(h),(i) given above (300 words)
Instructions for the excel file , demonstrate you can make summaries without using the automatic dataset summarizer
a) Paste in your dataset into the excel file
b) Use a pivot table to make a summary that lets you investigate the relationship between the variables “Which region?” and “How much would they pay for version 1”
c) Make a graph that lets you investigate the relationship between the variables
“How much they would pay for version 1” and “How much would they pay for version 2”.
d) Use a pivot table to make a summary that lets you investigate the relationship between the variables “Which region?” and “would you pay more for version 1”

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