Martha is starting to save for a new laptop. She has been keeping track of her savings every day. The graph shows the number of
days since she started keeping track and the amount of money in her savings.
She would like to figure out when she might have the $350 she needs to buy the laptop. She wonders if she could use her new math skills on linear regression to help figure it out.
What do you think? Would a linear model be appropriate for this data?
She would like to figure out when she might have the $350 she needs to buy the laptop. She wonders if she could use her new math skills on linear regression to help figure it out.
What do you think? Would a linear model be appropriate for this data?
1 answer:
You might be interested in
Answer:
Step-by-step explanation:
The mean SAT score is , we are going to call it \mu since it's the "true" mean
The standard deviation (we are going to call it ) is
Next they draw a random sample of n=70 students, and they got a mean score (denoted by ) of
The test then boils down to the question if the score of 613 obtained by the students in the sample is statistically bigger that the "true" mean of 600.
- So the Null Hypothesis
- The alternative would be then the opposite
The test statistic for this type of test takes the form
and this test statistic follows a normal distribution. This last part is quite important because it will tell us where to look for the critical value. The problem ask for a 0.05 significance level. Looking at the normal distribution table, the critical value that leaves .05% in the upper tail is 1.645.
With this we can then replace the values in the test statistic and compare it to the critical value of 1.645.