A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Consequently, the appraiser decided to fit the simple linear regression model. E(y)equalsbeta 0plusbeta 1x, where y equals the appraised value of the house (in thousands of dollars) and x equals the number of rooms. What set of hypotheses would you test to determine whether the appraised value is positively linearly related to number of rooms?

Step-by-step explanation:

The slope represents how much y is predicted to change on average for each 1 unit in x.

y = appraised value of a house in East Meadow County

x = # of rooms

1 unit of x = 1 additional room

1 unit of y = $1,000

slope = 19.79

Each additional room in a house in East Meadow County is predicted to increase the appraised value by 19.79 x $1,000 = $19,790, on average.

Note: Since we only sampled homes in East Meadow County, our regression equation is only good to predict appraised values in that county. So, our interpretation must include that fact.

60

step-by-step explanation:

every triangle measures a total of 120 degrees. you have to find angle c. we know that isosceles triangles angles are equal. 60 degrees plus 60 degrees gives you 120.