i would like to get more explanation for these questions please? thank you

1) Conduct a descriptive analysis on any 2 interval /ratio variables you wish using Descriptive_Statistics.xls and Frequency_Distribution.xls. Explain the output.

Descriptive Statistics

1. Q3 sales 2019 Measures of Central Tendency - Mean (Also average, Sum of data items divided by number of data items) = 71160.28 - Median (Middle number in a data set) = 59868.00 - Mode (the data value that occurs most often in the data set) = N/A - Midrange (the average of the Minimum and maximum values) = 125417.50 Measures of Dispersion -Range (Difference between the maximum and the minimum.) = 177517.00 - Interquartile Range (Difference between the first and third quartiles) = 0.00 - Standard Deviation (Average weighted distance of all observations around the mean) = 41785.69 - Variance (The standard deviation squared) = 1746043870.79 - Coefficient of Variation (Gives a relative measure to the dispersion so you can determine if the standard deviation is truly large or small. It is computed as the standard deviation as a percentage of the mean) = 58.72% Other measure - Sample Size (The total number of observations in the sample.) = 32 - Minimum (The smallest number in the data set)= 36659.00 - Maximum (The largest number in the data set)= 214176.00 - First Quartile (The observation such that 25% of the data is less than its value and 75% is greater than its value) = 0.00 - Third Quartile (The observation such that 75% of the data is less than its value and 25% is greater than its value) = 0.00 - Given percentile (For the kth percentile, k % of the observations fall below this value) = 90%

Develop a model to predict an interval / ratio variable using at least 2 other variables. Use Multiple_Regression.xls and state the regression model and which variables are or are not significant. Also, use the model to make a prediction by making up values for each of the independent variables.

I used two variables, Q3 sales 2018 and Number of Cylinders, to regress many variables used to predict Q3 sales 2019. After running linear regression with the two variables above, the result is: Y = -1108.81 + 0.97*Q3 sales 2018 + 1208.62*Number of cylinders If we have:

- Q3 sales 2018: 50000

- Number of cylinders: 4

Y = -1108.81 + 0.97*50000 + 1208.62*4 = 52018 (cars)

But because in the above statistical results we see, the p-value of X2 (number of cylinders) is 0.172>0.05 => this variable should be remove and we have the new regression with just only one variable is Q3 Sales 2018

The new result is: Y = 3784.31 + 0.985*Q3 sales 2018 If we have:

- Q3 sales 2018: 50000 Y = 3784.31 + 0.985*50000 = 53028 (cars)

thank you