Stats 412 HW1 PDF

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Victor Omisore Stat 412, HW1

Question 1.

QUESTION 2

(a) Fitted regression model is, Y = 3.850904 - 0.036643 * X Where Y = log( Biological recovery ) (b) From R software output we see that estimate of = Residual standard error = 0.2564 (c) Standard errors are SE(B1) = 0.003801, SE(B0)= 0.134391

QUESTION 3 (used excel) (a) Plot the data in scatterplot

(b) Yes the linear model seems appropriate because the majority of the values is close to the straight line

(D continuation).. the t-test statistic = -5.39 and the p-value=0.000 Since the p-value is less than 0.05, the null hypothesis is rejected so therefore there appears to be a linear relationship between the amount of time needed to run a 10km and the time it takes to reach exhaustion on the treadmill. QUESTION 4

(a) In this case Price is the dependent variable while landing is the independent variable

price vs Landings y = -1.0644x + 13.832 R² = 0.164

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PRICE

10 8 6 4 2 0

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-0.8

-0.6

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-0.2

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0.8

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Landings

(b) The straight line seems to be a reasonable model because all the dots are somewhat close to the trendline (c) (c)The value of correlation coefficient is -0.40503, because this is a negative (inverse) correlation, it is an indication that both variables move in the opposite direction.

(d) The coefficient of determination is our Rsquare = 0.164, (e) R^2 of 0.2 is quite high for real-world data. It means that a full 20% of the variation of one variable is completely explained by the other.

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(f)

The slope for the graph is -0.154 because the slope is negative it means that two variables are negatively related; that is, when x increases, y decreases, and when x decreases, y increases....