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<h1>Reproducible Research: Peer Assessment 1</h1>
<h2>Loading and preprocessing the data</h2>
<p>We assume that the current directory contains the zipped data file 'activity.zip'. </p>
<p>Unzip it and load it:</p>
<pre><code class="r">unzip("activity.zip")
df <- read.csv("activity.csv")
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<p>Aggregate the data to get the total of steps per day:</p>
<pre><code class="r">steps.per.day <- aggregate(df$steps, list(df$date), sum, na.rm = T)
names(steps.per.day) <- c("date", "num.steps")
</code></pre>
<p>Histogram of the steps taken per day</p>
<pre><code class="r">hist(steps.per.day$num.steps, breaks = 10, main = "Histogram: number of steps per day",
xlab = "number of steps per day")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-3"/> </p>
<p>Calculate mean ond median of the total number of steps per day:</p>
<pre><code class="r">mean(steps.per.day$num.steps, na.rm = T)
</code></pre>
<pre><code>## [1] 9354
</code></pre>
<pre><code class="r">median(steps.per.day$num.steps, na.rm = T)
</code></pre>
<pre><code>## [1] 10395
</code></pre>
<h2>What is the average daily activity pattern?</h2>
<p>Aggregate the steps over the 5-minutes intervals, taking the mean over all days:</p>
<pre><code class="r">steps.per.interval <- aggregate(df$steps, list(df$interval), mean, na.rm = T)
names(steps.per.interval) <- c("interval", "mean.steps")
</code></pre>
<p>Plot the time series of the 5-minute interval and the average number of steps taken, averaged across all days.</p>
<pre><code class="r">plot(steps.per.interval$interval, steps.per.interval$mean.steps, t = "l", main = "Average steps per interval",
ylab = "Number of steps", xlab = "Interval")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-6"/> </p>
<p>Show the 5-minutes intervall with the most steps (averaged over all days):</p>
<pre><code class="r">steps.per.interval[steps.per.interval$mean.steps == max(steps.per.interval$mean.steps),
]
</code></pre>
<pre><code>## interval mean.steps
## 104 835 206.2
</code></pre>
<h2>Imputing missing values</h2>
<h3>Total number of missing values</h3>
<p>The steps-field has 2304 missing values, whereas both the date and interval fields have no missing values:</p>
<pre><code class="r">sum(is.na(df$steps))
</code></pre>
<pre><code>## [1] 2304
</code></pre>
<pre><code class="r">sum(is.na(df$date))
</code></pre>
<pre><code>## [1] 0
</code></pre>
<pre><code class="r">sum(is.na(df$interval))
</code></pre>
<pre><code>## [1] 0
</code></pre>
<h3>Replacing missing values</h3>
<p>Copy the datasest to a new data.frame <code>df.complete</code> and replace missing values with the mean of the 5-minutes-interval averaged over all days.</p>
<pre><code class="r">
df.complete <- df
for (i in 1:nrow(df)) {
if (is.na(df[i, 1])) {
df.complete[i, 1] <- steps.per.interval[steps.per.interval$interval ==
df[i, 3], ][2]
}
}
</code></pre>
<h3>Histogram of the steps taken per day, based on replaced missing values</h3>
<pre><code class="r">steps.per.day.complete <- aggregate(df.complete$steps, list(df.complete$date),
sum, na.rm = T)
names(steps.per.day.complete) <- c("date", "num.steps")
hist(steps.per.day.complete$num.steps, breaks = 10, main = "Histogram: number of steps per day",
xlab = "number of steps per day")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-10"/> </p>
<h3>Mean and median of steps taken per day, based on replaced missing values</h3>
<p>Calculate mean ond median of the total number of steps per day:</p>
<pre><code class="r">mean(steps.per.day.complete$num.steps, na.rm = T)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<pre><code class="r">median(steps.per.day.complete$num.steps, na.rm = T)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<h4>Changes introduced by replacing missing values:</h4>
<p>Days without a single steps measurement (i.e. only NAs) show up as having 0 steps in the histogram.<br/>
With missing values replaced by the mean of the interval over the days, such days with seemingly
0 steps disappear.<br/>
With missing values, the mean is 9354 and the median 10395.<br/>
Without missing values, both mean and median are 10766.</p>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<p>Create a new factor variable in the dataset with two levels – “weekday” and “weekend” indicating whether a given date is a weekday or weekend day.</p>
<pre><code class="r">weekend <- weekdays(as.Date(df.complete$date)) == "Saturday" | weekdays(as.Date(df.complete$date)) ==
"Sunday"
df.complete$weekend <- factor(weekend, levels = c(FALSE, TRUE), labels = c("weekday",
"weekend"))
</code></pre>
<p>Number of steps per interval averaged over weekdays and over weekends:</p>
<pre><code class="r">spiw <- aggregate(df.complete$steps, list(df.complete$weekend, df.complete$interval),
mean, na.rm = T)
library(lattice)
names(spiw) <- c("weekend", "interval", "mean.steps")
xyplot(mean.steps ~ interval | weekend, data = spiw, type = "b", layout = c(1,
2), xlab = "Interval", ylab = "Number of steps", pch = "")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-13"/> </p>
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