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<!DOCTYPE html>
<head>
<meta charset='utf-8'/>
<script async='async' src='https://cdn.datacamp.com/dcl-react-dev.js.gz'></script>
<style>
.DCexercise .datacamp-exercise {
border: 2px solid #3D678D;
border-radius: 10px 10px 10px 10px !important;
}
*[class*="lm_"], .ace_gutter, textarea[class*="ace_"], .ace_scroller {
background-color: #F0EFF0 !important;
}
div[class*="Editor-module__editor"], div[class*="dcl__Footer"] {
background-color: #3D678D !important;
}
*[class*="lm_"] {
border-radius: 10px 10px 0px 0px !important;
}
div[class*="dcl__Footer"] {
border-radius: 0px 0px 10px 10px !important;
}
.lm_content {
border-radius: 0px !important;
}
.lm_splitter {
background-color: #3D678D !important;
width: 3px !important;
}
.lm_drag_handle {
background: transparent !important;
}
div[class*="dcl__index-module"] {
outline-color: transparent !important;
border-radius: 10px !important;
}
button[class*="secondary-light"] {
background-color: #FF0000;
}
</style>
</head>
<body>
<div data-datacamp-exercise data-lang='r' data-height =320><code data-type="pre-exercise-code">
cs <- c(23, 19, 30, 22, 23, 29, 35, 36, 33, 25)
ts <- c(430, 430, 333, 410, 390, 377, 325, 310, 328, 375)
mod <- lm(ts ~ cs)
</code>
<code data-type="sample-code">
# assign the model summary to the variable `s`
# check names of entries in `s`
# save the R^2 of the regression to the variable `R2`
</code>
<code data-type="solution">
# assign the model summary to the variable `s`
s <- summary(mod)
# check names of entries in `s`
names(s)
# save the R^2 of the regression to the variable `R2`
R2 <- s$r.squared
</code>
<code data-type="sct">
test_predefined_objects("mod")
test_function("names", args = "x")
test_object("s")
test_object("R2")
</code></div>
</body>
</html>