High Standard Deviation for Foreign Cars: Descriptive Statistics

The standard deviation seems to be higher contrary to the case in mean in each and every variable that indicate the amount of the variation experienced in the information. In the same way, there are high values in the range and this indicates a fine spread.

For foreign cars,

There is kind of similarity in all of the three variables and this similarity is seen in the descriptive nature of the statistics.

The standard deviation is higher as compared to mean in each case and this indicates that the variation level in the available data. The range also has higher values and this shows the fine spread.

In the comparison of the two car types, we can note that the mean list price, days to make sales and sale price of the foreign vehicles is higher than the mean list price, the days to make sales and the prices for the domestic cars and as such there is an expectation of prices that are high for foreign vehicles as compared to the domestic ones. We can therefore do a test of the difference of the men test between the foreign and domestic cars and it may be known whether the foreign cars have higher sale prices contrary to the domestic vehicles.

2. Confidence Intervals

For domestic cars,

Margin of error = 49.1826 - 44.7610 =4.4216

Here not much margin of error is notable. . It will increase depending on the confidence level.

Margin of error = 52.1198 - 47.5950 = 4.5248

Here not much high margin of error notable. It will increase depending on confidence level.

For foreign cars,

Margin of error = 49.6340 - 45.1540 = 4.48

Here margin of error is not that much high. It will increase with level of confidence.

Margin of error = 52.3613 - 48.39 =3.97

Here margin of error is not that much high. It will increase with level of confidence.

Sample size for domestic cars

Margin error = 7 = t (0.01) * SD (days to sell)/n^0.5

n= (t (0.01) * SD (days to sell)/7) ^2

n= 102.7 ~103

Sample size for foreign cars

Margin error = 8 = t (0.01) * SD (days to sell)/n^0.5

n= (t (0.01) * SD (days to sell)/8) ^2

n= 60.8 ~ 61

Z score is calculated by subtracting the mean from value and dividing the difference by standard deviation.

Z score for domestic cars Z score for foreign cars

List Price in K Sale Price in K Days to Sell List Price in K Sale Price in K Days to Sell

0.516791 0.432858 -1.08504 -1.05294 -1.10259 -1.80833

-1.0653 -1.01125 -0.79179 -0.75882 -0.80259 1.65

0.509328 0.579145 1.517595 1.557353 1.456667 1.275

0.416045 0.436609 0.271261 0.307353 0.282593 1.191667

-0.33769 -0.27232 -1.3783 -1.34706 -1.42481 -0.14167

-1.50187 -1.46137 0.711144 0.748529 0.66037 -0.80833

-0.52799 -0.57239 -0.68182 -0.64853 -0.69889 0.066667

0.860075 0.916729 1.554252 1.594118 1.512222 -1.225

-1.01306 -0.96624 0.454545 0.491176 0.46037 0.566667

0.065299 0.042761 1.041056 1.079412 1.015926 -1.26667

1.628731 1.614404 1.077713 1.116176 1.152963 1.025

-1.4944 -1.53638 -0.82845 -0.79559 -0.82481 -1.43333

0.703358 0.762941 -0.57185 -0.53824 -0.57667 1.608333

-0.68843 -0.66617 -1.01173 -0.97941 -0.97296 -1.6

-1.02799 -1.08627 -1.41496 -1.38382 -1.34333 -1.14167

0.169776 0.24156 -1.3783 -1.34706 -1.38778 0.316667

1.561567 1.501875 1.334311 1.373529 1.401111 -1.225

0.158582 0.211553 -1.15836 -1.12647 -1.15444 -0.55833

-0.61754 -0.59865 -0.79179 -0.75882 -0.8137 1.233333

1.039179 0.946737 -0.38856 -0.35441 -0.40259 -0.725

0.06903 -0.02101 -0.02199 0.013235 0.041852 -1.14167

-1.16231 -1.15754 -0.09531 -0.06029 -0.14333 -0.725

-0.46828 -0.45236 1.041056 1.079412 1.104815 -0.05833

-1.35634 -1.30758 -0.20528 -0.17059 -0.13222 -0.14167

-0.88619 -0.87622 -1.34164 -1.31029 -1.35815 0.983333

-0.3041 -0.35859 -0.42522 -0.39118 -0.39519 1.108333

-1.05037 -1.01875 -0.46188 -0.42794 -0.45444 -0.475

0.04291 0.050263 -1.01173 -0.97941 -0.94704 0.65

-0.43843 -0.3811 0.894428 0.932353 0.852963 0.691667

1.733209 1.779445 1.22434 1.263235 1.171481 0.566667

-0.76679 -0.74119 1.11437 1.152941 1.167778 0.983333

1.046642 1.108027 -1.52493 -1.49412 -1.52481 1.566667

-1.61007 -1.54764 1.077713 1.116176 1.101111 -0.18333

-0.49067 -0.44111 -0.49853 -0.46471 -0.56556 1.066667

1.26306 1.28057 -1.26833 -1.23676 -1.21 0.9

-0.26306 -0.30233 0.491202 0.527941 0.438148 1.15

1.151119 0.946737 -0.53519 -0.50147 -0.6137 -0.35

0.121269 0.03901 0.564516 0.601471 0.556667 -0.68333

-0.17351 -0.13728 0.16129 0.197059 0.141852 -0.05833

-0.31157 -0.24606 -0.16862 -0.13382 -0.08407 -1.43333

-1.12127 -1.1838 -1.1217 -1.08971 -1.20259 0.566667

-0.02425 -0.03226 1.004399 1.042647 1.075185 -0.76667

-0.62127 -0.65491 0.564516 0.601471 0.534444 0.525

-0.08022 -0.17854 1.004399 1.042647 0.982593 1.233333

1.050373 1.096774 -1.59824 -1.56765 -1.54333 -0.14167

-1.58396 -1.51013 -1.15836 -1.12647 -1.12852 -0.225

-0.27425 -0.31358 -1.26833 -1.23676 -1.20259 0.275

-1.49067 -1.56639 -1.08504 -1.05294 -1.02111 0.9

1.065299 1.044261 0.564516 0.601471 0.630741 -0.85

-1.55037 -1.49887 0.307918 0.344118 0.275185 -0.1

0.188433 0.185296 0.381232 0.417647 0.408519 -0.64167

0.195896 0.155289 0.527859 0.564706 0.501111 -1.1

-1.53545 -1.50638 -0.27859 -0.24412 -0.26556 -0.30833

-0.39366 -0.48987 1.517595 1.557353 1.49 -1.93333

1.222015 1.183046 -0.93842 -0.90588 -0.92481 0.316667

1.48694 1.490623 1.480938 1.520588 1.545556 -1.64167

0.740672 0.665416 1.370968 1.410294 1.334444 1.108333

1.229478 1.194299 0.821114 0.858824 0.734444 0.941667

0.076493 0.15904 -0.6085 -0.575 -0.58037 1.358333

-0.57276 -0.53488 -0.13196 -0.09706 -0.22852 0.025

-0.75933 -0.71118 0.087977 0.123529 -0.00259 -0.35

-1.48694 -1.46887 -0.8651 -0.83235 -0.83593 1.525

1.352612 1.415604 1.444282 1.483824 1.430741 0.15

0.322761 0.376594 -1.19501 -1.16324 -1.29148 0.191667

-1.05037 -1.14254 -1.52493 -1.49412 -1.61741 -0.26667

0.666045 0.594149 0.63783 0.675 0.623333 0.858333

-0.78545 -0.77494 -1.1217 -1.08971 -1.05074 -1.89167

1.333955 1.288072 1.407625 1.447059 1.482593 -0.18333

1.710821 1.715679 -1.26833 -1.23676 -1.34704 1.483333

-1.65858 -1.59265 -1.70821 -1.53088 -1.5063 0.733333

0.102612 0.166542 1.22434 1.263235 1.308519 0.275

0.751866 0.747937 1.480938 1.520588 1.475185 0.4

-0.41604 -0.47487 1.22434 1.263235 1.182593 0.983333

-0.41231 -0.38485 1.22434 1.263235 1.21963 0.775

0.330224 0.387847 0.234604 0.270588 0.19 -1.51667

1.151119 0.946737 -1.08504 -1.05294 -1.08037 -0.64167

-1.21455 -1.15379 1.004399 1.042647 1.052963 0.15

0.714552 0.657914 1.004399 1.042647 1.045556 -0.18333

1.70709 1.618155 0.124633 0.160294 0.134444 -0.68333

-0.94963 -0.95499 0.014663 0.05 -0.03963 1.066667

1.509328 1.453113 0.857771 0.895588 0.908519 -0.68333

0.669776 0.702926 1.22434 1.263235 1.208519 0.025

-1.5541 -1.49512 -0.13196 -0.09706 -0.17667 -0.05833

0.904851 0.87922 1.041056 1.079412 1.11963 -1.39167

-0.26679 -0.18605 -1.59824 -1.56765 -1.55074 1.025