(a) Identtify and itnerperet the slope of this regression line. 2.74 (b) Identify and interpret the y intercept: 45.28

(a) Identtify and itnerperet the slope of this regression line. -8.54 (b) Identify and interpret the y intercept: 45.55

(b) Calculate the value of the correlation coefficien. What does it tell you about the reatlionship between x and y? 0.93, 93% this means that this is a linear srong positive relationship. because it is above 0.75

(c) Determine the least squares regression line y on x. Draw your regression line on your scatter plot. y=2.31x+25.67

(d) Identify and interpret the slope of the regression line 2.31 (e) Identify and interpret the y intercept. 25.67, if the x variable is 0, then the y value is expected to be 25.67

(b) Calculate the value of the correlatio ncoefficient 0.97, or 97% this is a strong correlation as it is above 0.75, and predicts a strong positive relationship between diet time and weight gain.

(c) Determine the equation of the leasts quares lien that models the realtionsihp between the time i nweeks and the wiegght gain for the data provided. Draw this line on yoru scater plot

(d) Identify and itnerpet the gradient 9.12

(e) identify and interpert the vertical axis intercept. 51.47

(a) identify E.V and R.V Average Temperature = E.V Profit = R.V

(b) Does there appear to be a realtionship, Refer to calculator yes, there appears to be asgnificant correlation between the two variables, they follow the least squares regression line very closely on my calculator’s graph.

(c) the correlation coefficient (r) came out as 0.967, which indicates a strong posotive correlation

(e) Identify and itnerpret the gradient of the leasts squares regression line in this context. 1.26, everytime the x variable increases by 1, the y variable increases by 1.26 (f) Identify and itnerpret the vertical axis intercept -4.48

(A) identify E.V and R.V Age = E.V Price = R.V

(b) Does there relationship, graph on calc do not draw. this appears to be a pretty strong negative assosciation, I’d estimate around -0.86

(c) Calculate r -0.96, this means that it is a strong negative relationshi pas it is below -0.75

(d) etermine the equation

(e) Identify and itnerpret the slope of the least squares regression line -0.66 (f) idetnify and the interpet the vertica axis 13.11 (g) identifyhorizontal axis

(c) t = 1.05m+0.45

Usign the line in this example their mark would come otu to be somewere around 64%

(d) No my answer above will not be the same as other class members as ta line of best fit drawn by eye is not objective.