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What can you tell about the answers , when calculating mean, mode, median from the graph that shows number of cars sold per month?
What can you tell about the answers , when calculating mean, mode, median from the graph that shows number of cars sold per month?
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ChatGPT
Aug 13
When calculating the mean, mode, and median from a graph that shows the number of cars sold per month, you can determine the average number of cars sold, the most frequently occurring number of cars sold, and the middle number of cars sold.
The mean is calculated by adding up all the numbers of cars sold in each month and dividing by the total number of months. This will give you an average number of cars sold per month.
The mode is the number of cars sold that appears most frequently in the data set. This can give you an idea of the most common number of cars sold in a month.
The median is the middle number in a data set when the numbers are arranged in order. This can give you an idea of the typical number of cars sold in a month, as it is not affected by extreme values.
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Google Gemini AI
Aug 13
Mean:
- The mean is the average of all the data points. - On a graph, the mean can be visually estimated as the point where the line of best fit intersects the x-axis. - In a distribution with a normal distribution, the mean is the highest point on the graph.
Mode:
- The mode is the most frequently occurring data point. - On a graph, the mode is the peak of the distribution.
Median:
- The median is the middle value of the data set. - On a graph, the median can be visually estimated as the point where the line of best fit divides the area under the curve in half.
Additional Observations:
- Shape of the distribution: The shape of the distribution can give an indication of the spread of the data. A normal distribution is bell-shaped, while a skewed distribution has a longer tail on one side. - Outliers: Outliers are extreme data points that lie far from the rest of the data. Outliers can affect the mean, but not the mode or median. - Skewness: Skewness refers to the asymmetry of a distribution. A distribution can be positively skewed (right-tailed) or negatively skewed (left-tailed). Skewness can affect the mean and median, but not the mode.