Question

(у-у)2 127.6 0.744902 352.8618 -16.2126 124 0.15451 230.5725 5.96872 110.8 0.026594 3.938698 -0.32364 103.9 0.005917 24.16101 -0.37811 101.5 0.10044 53.51485 -2.31841 130.1 0.744902 453.0349 -18.3703 122 0.15451 173.8341 -5.18257 92.3 0.321402 272.7579 -9.36295 113.1 0.026594 18.35793 -0.69872 83.7 1.181402 630.7825 -27.2985 128 0.744902 368.0495 -16.5578 91.4 0.321402 303.2956 9.87318 86.2 1.181402 511.4556 -24.5812 (x-X)" (х-х)(у-у) 0.01 0.48 0.71 0.95 1.19 0.01 0.48 1.44 0.71 1.96 0.01 1.44 1.96 ЕК х-х х-х total sum 11.35 1414.6 5.7088773396.617 -137.127 mean 0.873077 108.8154SSxx SSyy SSxy

Statistics/Computer Science:

With a given data set (X,Y) how and what is the code to use in R/Rstudio to receive these results (aka ANOVA)?

Answer 1

X=c(0.01,0.48,0.71,0.95,1.19,0.01,0.48,1.44,0.71,1.96,0.01,1.44,1.96)

Y=c(127.6,124,110.8,103.9,101.5,130.1,122,92.3,113.1,83.7,128,91.4,86.2)

## For intercept and slope
model=lm(Y~X)
summary(model)

#### For ANOVA table required for your
model.aov=aov(Y~X)
summary(model.aov)

#### Run

> X=c(0.01,0.48,0.71,0.95,1.19,0.01,0.48,1.44,0.71,1.96,0.01,1.44,1.96)
>
> Y=c(127.6,124,110.8,103.9,101.5,130.1,122,92.3,113.1,83.7,128,91.4,86.2)
>
> ## For intercept and slope
> model=lm(Y~X)
> summary(model)

Call:
lm(formula = Y ~ X)

Residuals:
Min 1Q Median 3Q Max
-3.7980 -1.9464 0.2971 0.9924 5.7429

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 129.787 1.403 92.52 < 2e-16 ***
X -24.020 1.280 -18.77 1.06e-09 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.058 on 11 degrees of freedom
Multiple R-squared: 0.9697, Adjusted R-squared: 0.967
F-statistic: 352.3 on 1 and 11 DF, p-value: 1.055e-09

>
> #### For ANOVA table required for your
> model.aov=aov(Y~X)
> summary(model.aov)
Df Sum Sq Mean Sq F value Pr(>F)
X 1 3294 3294 352.3 1.06e-09 ***
Residuals 11 103 9   
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>