To determine if the data is symmetric, skewed, or uniform, we can create a histogram of the data and visually assess its shape.
Here is the histogram of the given data set:
- Range: 3.5 - 52.5
- Number of bins: 5
- Bin widths: 10
```
0 | 0
1 | 0
2 | 2 **
3 | 1 *
4 | 1 *
5 | 1 *
6 | 0
7 | 1 *
8 | 0
9 | 1 *
```
Based on the histogram, we can see that the data is not symmetric. It is also not uniform, as the frequencies are not evenly distributed across the bins. This data set is skewed to the left, as the distribution is elongated towards the lower end of the range.
Task 3) look at a a histogram of this data set 36, 45, 26, 35.5, 44, 39, 43.5, 45.5, 41, 35.5, 31.5, 40.5, 49, 35, 32, 28.5, 26.5, 25, 35.5, 27, 28.5, 11, 3.5, 12.5, 14, 22.5, 24, 49, 52.5, 40, 47
is the data symmetric skewed or uniform
3 answers
what feature of the data makes the histogram data that shape??
The shape of the histogram is influenced by the presence of outliers and the distribution of the data points across the range. In this specific dataset, the presence of outlier values such as 3.5 and 52.5 can contribute to skewness in the data.
Furthermore, the distribution of the data points towards the lower end of the range (e.g., lower values such as 11, 3.5, 12.5, 14, etc.) compared to the higher end of the range (e.g., higher values such as 47, 49, 52.5) also contributes to the left skewness of the histogram.
In summary, the presence of outliers and the distribution of data points towards one end of the range (in this case, the lower end) can result in a skewed shape in the histogram.
Furthermore, the distribution of the data points towards the lower end of the range (e.g., lower values such as 11, 3.5, 12.5, 14, etc.) compared to the higher end of the range (e.g., higher values such as 47, 49, 52.5) also contributes to the left skewness of the histogram.
In summary, the presence of outliers and the distribution of data points towards one end of the range (in this case, the lower end) can result in a skewed shape in the histogram.