Janice is considering buying a new home. She wants to estimate the monthly utilities (heating and air conditioning). She figures
that the utilities are dependent on the size (square footage) of the home. She collects data on 10 homes in the neighborhood and finds a linear model to give the relationship between the size of the home and the monthly utilities. The equation of the line is ŷ = –8.1 + 1.91x, where ŷ is the mean monthly cost in utilities and x is the square footage of the home. The residual plot is shown.
Based on the residual plot, is the linear model appropriate?
No, there is no clear pattern in the residual plot.
Yes, there is no clear pattern in the residual plot.
No, there are no homes between 2,300 and 2,900 square feet.
Yes, half of the residuals are positive and half are negative.
I think its (A), can someone confirm?
Based on the residual plot, is the linear model appropriate?
No, there is no clear pattern in the residual plot.
Yes, there is no clear pattern in the residual plot.
No, there are no homes between 2,300 and 2,900 square feet.
Yes, half of the residuals are positive and half are negative.
I think its (A), can someone confirm?
1 answer:
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Answer:
a
The 95% confidence interval is
b
The sample proportion is
c
The critical value is
d
The standard error is
Step-by-step explanation:
From the question we are told that
The sample size is n = 200
The number of defective is k = 18
The null hypothesis is
The alternative hypothesis is
Generally the sample proportion is mathematically evaluated as
Given that the confidence level is 95% then the level of significance is mathematically evaluated as
Next we obtain the critical value of from the normal distribution table, the value is
Generally the standard of error is mathematically represented as
substituting values
The margin of error is
=>
=>
The 95% confidence interval is mathematically represented as
=>
=>