You may assume the conditions for regression inference are satisfied. A grass seed company conducts a study to determine the relationship between the density of seeds planted (in pounds per 500 sq ft) and the quality of the resulting lawn. Eight similar plots of land are selected and each is planted with a particular density of seed. One month later the quality of each lawn is rated on a scale of 0 to 100. The sample data are given below. Seed Density Lawn Quality
1 30
1 40
2 40
3 40
3 50
3 65
4 50
5 50
At the 1% level of significance, is there evidence of an association between seed density and lawn quality?
a) yes
b) no

b) no

Step-by-step explanation:

The regression analysis is a statistical technique which is used for forecasting. It determines the relationship between two variables. It determines the relationship of two or more dependent and independent variables. It is widely used in stats to find trend in the data. It helps to predict the values of dependent and independent variables. In the given question, the relationship is determined to identify the relationship between density of seed planted and quality of lawn. The significance level is 1% which means strength of evidence is not strong enough to support the test.

b. y = 4x - 2

step-by-step explanation:

to find a parallel equation to an equation, make sure both equations have the same slope but different y-intercepts.

y = 4x + 1

4 = slope

1 = y-intercept

y = 4x - 2

4 = slope

-2 = y-intercept

they both have the same slope but different y-intercepts, so, b. is the correct answer.

and to check your work, you can graph both equations. : )