determine whether the data in the table appears to be positively skewed, negatively skewed, or normally distributed. explain
What table?
To determine whether the data in a table appears to be positively skewed, negatively skewed, or normally distributed, you will need to examine the shape of the data distribution.
Here's how you can do it:
1. Visualize the data: Create a histogram or a bar chart to visualize the distribution of the data. A histogram is a graphical representation that displays the frequency or count of data points in different intervals or bins.
2. Analyze the shape: Look at the shape of the histogram. If the data distribution is positively skewed, it means that the tail of the distribution extends more towards the right side of the histogram. The majority of the data points will be on the left side of the distribution, and the right tail will be longer. Conversely, if the data is negatively skewed, the tail of the distribution extends more towards the left side of the histogram. The majority of the data points will be on the right side of the distribution, and the left tail will be longer. If the data is normally distributed, the histogram will exhibit a bell-shaped curve where the data is distributed symmetrically around the mean.
3. Use statistical measures: You can also use statistical measures to validate your observations. Measures such as skewness and kurtosis can provide numerical indications of the distribution's shape. Skewness measures the asymmetry of the data distribution. A positive skewness value indicates positively skewed data, while a negative skewness value indicates negatively skewed data. A skewness value close to zero suggests a relatively symmetric distribution. Kurtosis measures the shape of the distribution's tails. A positive kurtosis value indicates heavy tails or more outliers, while a negative kurtosis value indicates lighter tails.
By examining the shape of the histogram and using statistical measures, you can determine whether the data in the table appears to be positively skewed, negatively skewed, or normally distributed. Remember that these are just visual and statistical indicators, and additional analysis might be required for a more thorough evaluation.