Lock, Statistics: Unlocking the Power of Data, 2 Help 1 System Announcements Cha

Question

Lock, Statistics: Unlocking the Power of Data, 2 Help 1 System Announcements Chapter 9, Section 1, Exercise 021 Using pH in Lakes as a Predictor of Mercury in Fish The FloridaLakes dataset includes data on 53 lakes in Florida. Two ?sample of fsh from each lake) We wish to use the pH of the lake water (which easy to measure) to predia average merary esesn hn, men naar to A scatterplot of the data isshown below and we see that the conditions for fitting a linear model are reasonably met. Computer output for the regression analysis below. of the variables recorded were pH (acidity of the lake water) and AvpMercury (average mern The regression equation is AvgMercury 1-53-01 52 pH. Predictor Coef SE Coef TP Constant 1.5309 0.2035 7.52 0.000 pH-0.15230 0.03031-5.02 0.000 S-0281645 R-Sq-33.1% R-Sq (adj) 31.8% cick here for the dataset associated with this question 9 TYUO P wER

Explanation / Answer

SolutionA:

regression model is

Avg memory=1.53-0.152(pH)

Given Ph=6.3

subst in Regression equation

Avg memory=1.53-0.152(6.3)

Avg Memory=0.5724=0.572(tto 3 decimals)

Solutionb:

slope=-0.152

Intrrepretation is

For unit increase in pH ,average memory decreases by 0.152 units

Solutionc

t=-5.02

p=0.000

Reject Ho

Solutione:

R sq=33.1%

33.1% variation in Avg memory is explained by pH.

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