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STA 2023 Elementary Statistics STA 2023 final exam review with Varified Solutions $14.99   Add to cart

Exam (elaborations)

STA 2023 Elementary Statistics STA 2023 final exam review with Varified Solutions

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STA 2023 Elementary Statistics

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  • October 11, 2024
  • 23
  • 2024/2025
  • Exam (elaborations)
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Quiz Submissions - Final Review


point
Determine type and strength of the association.
Data shown on the following scatter-plot indicate a correlation
of 0.96 between the average flow rate and pressure.
Describe the association.




Question options:
ve correlation


of a correlation


ive correlation


ive correlation


ve correlation



Find the correlation coefficient.

A group of persons filled in a questionnaire their age and the
number of states they visited. The results are recorded in the
table below.



Question options:

, Interpret the correlation coefficient.
The correlation between a person’s annual income and debt level is high and positive.

Therefore, it can be concluded that:
Question options:
igher annual incomes tend to have more debt.

ge enough incomes do not have any debt.


me will cause a person to go into debt.


her annual incomes tend to have less debt.




Determine the point estimate.
It has been determined with 95% confidence that the
proportion of Americans who eat turkey on Thanksgiving is
between 0.78 and 0.82.
Determine the sample proportion that was used to build this
confidence interval.
Question options:

, Determine the specified confidence interval.

It has been estimated, with 90% confidence, the proportion of Americans
who go out shopping on Black Friday is 0.40 with a margin of error equal
to 0.04.
Determine the resulting 90% confidence interval for the proportion of
Americans who go out shopping on Black Friday.

Question options:




Construct the equation of the regression line.
An editing firm compiled the following table which lists the
number of pages contained in a piece of technical writing and
the cost of proofreading and correcting them (in dollars).
Assume there is a significant linear relationship between X and
Y and construct the equation of the linear regression line.

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