Question

Compare the values for mean and median commute times that you calculated.What can you infer about this frequency distribution

Help with question 12 and 13

Question 12 1 pts Compare the values for mean and median commute times that you calculated in questions 9 and 10. What can you infer about this frequency distribution It is bimodal. 0 It is symmetric. It is right (positive) skewed It is left (negative) skewed

Answer 1

In Question 9 in which we have already got Mean = 42.67 and

in Question 10 , we got median = 21 .That means, here (Mean > Median) .

Firstly, going with Question 12 in which our frequency distribution is right (positive) skewed because

in a right (positive) skewed distribution: Mean >Median >Mode.

Here, frequency distribution can not be left (negative) skewed distribution because in a left (negative) distribution : Mode >Median >Mean , which can not be applicable here.

Our frequency distribution can not be bimodal because there is not two modes are available.

Here, frequency distribution can not be symmetric because in a symmetric distribution Mean = Median, which is not applicable here.

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Now, moving to Question 13,

Firstly Lets discuss about Mean, It is the sum of observations divided by number of observations .

From above statement we know that mean is a value that depends on each values of observations available in a set of data also it's one big merit is that it is easy to understand and calculations .

The value of mean get fluctuated by the fluctuations of sampling, that means it is a very stable average.Thus, from above statements we see that Mean satisfies all the properties for being an ideal average. Therefore, we can say that Mean is the better description for the Central Tendency (location)

Now ,discussing about Median, it is the value of the variable which divides it into two equal parts. It is also easy to understand and easy to do calculate as like mean . It is not affected by extreme values of the variables.

Median is the only average to be used while dealing with qualitative data which cannot be quantitatively but still can be arranged in ascending or descending order of it's magnitude . Thus, discussing about these special and unique properties of median , we can say that Median is the better description of the Central Tendency(Location) .

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Standard Deviation : It is the square root of the arithmetic mean of the squares of the deviations of the given value from their arithmetic mean. Here, the steps of squaring the deviations overcomes the drawback of ignoring the signs in mean deviations. It is the only measure that affected least by the fluctuations of sampling. Thus, we can see that it satisfies the most or almost properties for an ideal measure of dispersion or variability.