The invasive diatom species Didymosphenia geminata has the potential to inflict substantial ecological and economic damage in rivers. The article “Substrate Characteristics Affect Colonization by the...

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The invasive diatom species Didymosphenia geminata has the potential to inflict substantial ecological and economic damage in rivers. The article “Substrate Characteristics Affect Colonization by the Bloom-Forming Didymosphenia geminata” (Aquatic Ecology, 2010: 33–40) described an investigation of colonization behavior. One aspect of particular interest was whether y = colony density was related to x = rock surface area. The article contained a scatterplot and summary of a regression analysis. Here is representative data:


a. Determine the equation of the least squares line for this data and then calculate and interpret the coefficient of determination.


b. The second observation has a very extreme y value (in the full data set consisting of 72 observations, there were 2 of these). This observation may have had a substantial impact on the form of the regression function and subsequent conclusions. Eliminate it and redo part (a). What do you conclude?




Answered Same DayDec 27, 2021

Answer To: The invasive diatom species Didymosphenia geminata has the potential to inflict substantial...

Robert answered on Dec 27 2021
107 Votes
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Part A
x y xy x2 y2
50 152 7600 2500 23104
71 1929 136959 5041 372
1041
55 48 2640 3025 2304
50 22 1100 2500 484
33 2 66 1089 4
58 5 290 3364 25
79 35 2765 6241 1225
26 7 182 676 49
69 269 18561 4761 72361
44 38 1672 1936 1444
37 171 6327 1369 29241
70 13 910 4900 169
20 43 860 400 1849
45 185 8325 2025 34225
49 25 1225 2401 625∑
xi =

yi =

xiyi =

x2i =

y2i =
756 2944 189482 42228 3888150
Least Squares Regression Equation : ŷ = b0 + b1x
b1 =
n

xy − (

x)(

y)
n

x2 − (

x)2
= 15(189482)− (756)(2944)15(42228)− (756)2
= 2842230− 2225664633420− 571536 =
616566
61884 ≈ 9.963254 ≈ 9.9633
Slope term, b1 = 9.9633
b0 = ȳ − b1x̄ =

y
n
− b1

x
n
= 294415 − (9.963254)
756
15 ≈ −305.881326 ≈ −305.8813
Intercept term, b0 = −305.8813
Least Squares Regression Eqn: ŷ = −305.8813 + (9.9633)x
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