The mode cannot be definitively determined with just the mean and median provided. However, in a dataset where the mean is 5 and the median is 6, it suggests that there may be some lower values pulling the mean down. The mode could be less than, equal to, or greater than both the mean and median depending on the distribution of the data. Therefore, without additional information about the dataset, the mode remains indeterminate.
mean is the average of numbers in the data set mode is the most frequently occurring value in a data set and median is the middle number of the data set so you would use mean
Subtracting the same amount from each value in a data set decreases the **mean**, *median*, and **mode** by that amount, but the **range** remains unchanged.
Quantitative data typically has a mean, median, and mode, but there are specific scenarios where these measures might not apply meaningfully. For example, if all values in a dataset are identical, the mean and median would equal that value, but there would be no mode in the traditional sense. Additionally, in the case of an empty dataset, there would be no mean, median, or mode, as there are no values to calculate these statistics from. However, in general practice, quantitative data usually allows for the calculation of these measures.
In a normal distribution the mean, median and mode are all the same value.
For the set 3 4 5 8 5, the mean median and mode all have the same value.
The mean (average value), the median (middle value), and the mode (most frequently occurring value) are all important values.
There would be a difference to the median. The old number wouldn't be the median but the mode wouldn't change. If the outlier is a high value, it will cause the mean value to shift to the higher side, while a low valued outlier will drop the mean value to a lower number.
mean is the average of numbers in the data set mode is the most frequently occurring value in a data set and median is the middle number of the data set so you would use mean
Subtracting the same amount from each value in a data set decreases the **mean**, *median*, and **mode** by that amount, but the **range** remains unchanged.
Quantitative data typically has a mean, median, and mode, but there are specific scenarios where these measures might not apply meaningfully. For example, if all values in a dataset are identical, the mean and median would equal that value, but there would be no mode in the traditional sense. Additionally, in the case of an empty dataset, there would be no mean, median, or mode, as there are no values to calculate these statistics from. However, in general practice, quantitative data usually allows for the calculation of these measures.
In a normal distribution the mean, median and mode are all the same value.
who discovered mean median and mode
For the set 3 4 5 8 5, the mean median and mode all have the same value.
In a normal distribution, the mean, median, and mode are all equal. Therefore, if both the mean and the mode are 25, the median would also be 25. This property is a defining characteristic of normal distributions.
they are all three types of averages: the mean is worked out by adding up all of the results and dividing it by the amount of results added up the median value is just the middle value of the results the mode value is the value that occurs most in the results
The median or mode should be used instead of the mean in distributions with extreme outliers. In such cases, the mean can be a misleading measure of central tendency and the median value or the mode value are typically more accurate measures.
Both median and mode are the statistics formulas, Median is called mid value of the given data and mode is the value which occure repetedly in the given data.