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Exercise 1. Using classical statistics describe the structure of monthly turnover of 80 shops [in tousand PLN].Calculate and interpret: arithmetic mean, standard deviation, coefficient of variability, coefficient of asymmetry (skewness) and coefficient of concentration (kurtosis).

Exercise 1. Using classical statistics describe the structure of monthly turnover of 80 shops [in tousand PLN].Calculate and interpret: arithmetic mean, standard deviation, coefficient of variability, coefficient of asymmetry (skewness) and coefficient of concentration (kurtosis).

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Exercise 1. Using classical statistics describe the structure of monthly turnover of 80 shops [in tousand PLN].Calculate and interpret: arithmetic mean, standard deviation, coefficient of variability, coefficient of asymmetry (skewness) and coefficient of concentration (kurtosis).

Exercise 2. Using positional statistics describe the structure of monthly turnover of 80 shops [in tousand PLN]Calculate and interpret: median, quartiles, deciles, quartile deviation, positional coefficient of variation, positional coefficient of asymmetry and positional coefficient of concentration.

Perform all calculations for the following data types:

  • individual data,
  • interval groupped data.
38 25 80 55 65 60 33 64
34 57 38 37 37 35 63 60
42 53 38 33 44 43 40 72
38 62 55 36 70 64 43 74
75 71 36 48 49 51 41 53
69 55 55 36 54 32 67 67
29 56 85 58 63 51 26 33
88 47 24 82 31 50 54 38
37 52 54 39 53 68 76 60
64 46 45 49 47 40 51 37

Exercise 3.

  • Calculate Pearson's correlation coefficient between expenditure (Y) and the income per 1 person (X).
  • Build a linear regression model describing the relationship between expenditure (Y) and income per 1 person (X):
    • estimate the structural parameters of the regression model,
    • interprete the regression coefficient,
    • determine the theoretical values and residuals from the estimated model.
Lp. Expenditures Income Lp. Expenditures Income
1 144 548 26 100 415
2 161 541 27 113 516
3 157 652 28 125 546
4 135 627 29 185 598
5 93 330 30 140 629
6 161 543 31 120 350
7 149 480 32 203 794
8 143 532 33 182 676
9 141 407 34 137 540
10 176 615 35 126 318
11 80 378 36 126 542
12 131 284 37 167 560
13 184 572 38 207 686
14 139 514 39 142 603
15 173 588 40 152 692
16 126 496 41 102 499
17 96 296 42 154 472
18 124 563 43 115 393
19 155 455 44 144 607
20 91 300 45 97 526
21 176 736 46 81 285
22 59 359 47 119 458
23 175 642 48 62 331
24 115 470 49 150 507
25 130 360 50 81 305

All measures should be interpreted. Accuracy of calculations - up to the thousandth.
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