Business Statistics Assignment Solution
VerifiedAdded on 2021/02/22
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AI Summary
This assignment provides a comprehensive solution to various business statistics problems. It covers topics such as calculating mean, median, mode, variance, and standard deviation, as well as testing hypotheses and interpreting p-values. The solutions are presented in a clear and concise manner, making it easier for students to understand and apply the concepts.
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Table of Contents
TASK...............................................................................................................................................3
1....................................................................................................................................................3
2....................................................................................................................................................4
3....................................................................................................................................................4
2....................................................................................................................................................4
3....................................................................................................................................................5
4....................................................................................................................................................5
TASK...............................................................................................................................................3
1....................................................................................................................................................3
2....................................................................................................................................................4
3....................................................................................................................................................4
2....................................................................................................................................................4
3....................................................................................................................................................5
4....................................................................................................................................................5
TASK
Q. 1.
1.
Range Frequency
0 - 3 10
4 - 6 18
7 - 9 26
10 - 12 30
13 - 15 48
16 - 18 40
19 - 21 22
22 - 24 18
25 - 27 6
28 - 30 2
31 - 33 0
Q. 1.
1.
Range Frequency
0 - 3 10
4 - 6 18
7 - 9 26
10 - 12 30
13 - 15 48
16 - 18 40
19 - 21 22
22 - 24 18
25 - 27 6
28 - 30 2
31 - 33 0
2.
Histogram shown in point (1) shows that range over 12 to 15 has highest frequency 48
while in over 30 range there is no data.
3.
Range X Frequency FX d= x-d F*D CF X2
0 - 3 2 10 20.00 -15 -150 10 4
4 - 6 5 18 90.00 -12 -216 28 25
7 - 9 8 26 208.00 -9 -234 54 64
10 - 12 11 30 330.00 -6 -180 84 121
13 - 15 14 48 672.00 -3 -144 132 196
16 - 18 17 40 680.00 0 0 172 289
19 - 21 20 22 440.00 3 66 194 400
22 - 24 23 18 414.00 6 108 212 529
0 4 7
0
10
20
30
40
50
60
10
18
26
30
48
40
22
18
6
2 0
Histogram shown in point (1) shows that range over 12 to 15 has highest frequency 48
while in over 30 range there is no data.
3.
Range X Frequency FX d= x-d F*D CF X2
0 - 3 2 10 20.00 -15 -150 10 4
4 - 6 5 18 90.00 -12 -216 28 25
7 - 9 8 26 208.00 -9 -234 54 64
10 - 12 11 30 330.00 -6 -180 84 121
13 - 15 14 48 672.00 -3 -144 132 196
16 - 18 17 40 680.00 0 0 172 289
19 - 21 20 22 440.00 3 66 194 400
22 - 24 23 18 414.00 6 108 212 529
0 4 7
0
10
20
30
40
50
60
10
18
26
30
48
40
22
18
6
2 0
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25 - 27 26 6 156.00 9 54 218 676
28 - 30 29 2 58.00 12 24 220 841
31 - 33 32 0 0.00 15 0 220 1024
187 220 3068.00 0 -672 4169
Mode = l + f1 – f2 * h
2f1 – f2 – f0
= 13 + (48-30)/(2*48 – 40 -30) * 3
= 13 + 2.07 = 15.07
Mean= A + Σ fd/ Σf * h
= 17 + [(-672) / 220 ] * 3
= 17 + (-9.16)
= 7.83
Median = l + (N/2 – cf) /f * h here, N/2 = 220/2 = 110, cf = 84, f = 48
= 13 + [(110 – 84) / 48] * 3
= 13 + 1.62
= 14.62
Q. 2.
1.
if SD 5.80 then mean will be 3.83
Variance = Σ x2 / Σf + (mean)2
(5.80)2 = 4169/220 + Mean2
33.64 = 18.95 + (Mean)2
Mean = √33.64-18.95
= 3.83
2.
Sd = √Σ x2 / Σf + (Σx/Σf)2
= √4169 / 220 + (187/220)2
= √18.95 + 0.72
= √19.67
= 4.4
28 - 30 29 2 58.00 12 24 220 841
31 - 33 32 0 0.00 15 0 220 1024
187 220 3068.00 0 -672 4169
Mode = l + f1 – f2 * h
2f1 – f2 – f0
= 13 + (48-30)/(2*48 – 40 -30) * 3
= 13 + 2.07 = 15.07
Mean= A + Σ fd/ Σf * h
= 17 + [(-672) / 220 ] * 3
= 17 + (-9.16)
= 7.83
Median = l + (N/2 – cf) /f * h here, N/2 = 220/2 = 110, cf = 84, f = 48
= 13 + [(110 – 84) / 48] * 3
= 13 + 1.62
= 14.62
Q. 2.
1.
if SD 5.80 then mean will be 3.83
Variance = Σ x2 / Σf + (mean)2
(5.80)2 = 4169/220 + Mean2
33.64 = 18.95 + (Mean)2
Mean = √33.64-18.95
= 3.83
2.
Sd = √Σ x2 / Σf + (Σx/Σf)2
= √4169 / 220 + (187/220)2
= √18.95 + 0.72
= √19.67
= 4.4
Q. 3.
1.
Sample size (n)= 30 H0 = 13
alpha = 0.05 H1 >13
rcrit (1-tailed) = 0.3061
rcrit (2-tailed) = 0.361
df = 28
2.
Condition to test Alternative Hypothesis
The population mean is less than the target. one sided: μ < 13
The population mean is greater than the target. one sided: μ > 13
The population mean differs from the target. two sided: μ ≠ 13
Since they want to ensure that days are not larger or smaller than 13 days, here individual
should chooses two-sided alternative hypothesis, which clear states that the population mean of
days are not equal to 13 cm. Formally, this is written as H1: μ ≠ 13
Q. 4.
Meaning of p value:
A p-value or probability value implies in context of statistical model to probability which
in case null hypothesis resulted true, statistical summary would be equivalent to or above
extreme than, actual ascertained outcomes.
Advantage of p value approach over critical value approach:
P-value approach is advantageous that as here need to compute one-value, P-value, in
order to conduct test. While critical-value approach, requirement to compute test-statistic and
critical value related to significance level.
Small p value indicate a strong relationship between variables:
A small p-value reflects statistical significance but does not reflect that alternative
hypothesis is ipso facto correct. So it clearly indicates a stronger relationship between variables.
1.
Sample size (n)= 30 H0 = 13
alpha = 0.05 H1 >13
rcrit (1-tailed) = 0.3061
rcrit (2-tailed) = 0.361
df = 28
2.
Condition to test Alternative Hypothesis
The population mean is less than the target. one sided: μ < 13
The population mean is greater than the target. one sided: μ > 13
The population mean differs from the target. two sided: μ ≠ 13
Since they want to ensure that days are not larger or smaller than 13 days, here individual
should chooses two-sided alternative hypothesis, which clear states that the population mean of
days are not equal to 13 cm. Formally, this is written as H1: μ ≠ 13
Q. 4.
Meaning of p value:
A p-value or probability value implies in context of statistical model to probability which
in case null hypothesis resulted true, statistical summary would be equivalent to or above
extreme than, actual ascertained outcomes.
Advantage of p value approach over critical value approach:
P-value approach is advantageous that as here need to compute one-value, P-value, in
order to conduct test. While critical-value approach, requirement to compute test-statistic and
critical value related to significance level.
Small p value indicate a strong relationship between variables:
A small p-value reflects statistical significance but does not reflect that alternative
hypothesis is ipso facto correct. So it clearly indicates a stronger relationship between variables.
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