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assignments for Rs.150 each
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Fall-2013
Master of
Business Administration - MBA Semester 1
MB0040–Statistics
for Management-4 Credits
(Book ID:
B1731)
Assignment
(60 Marks)
Note: Answers
for 10 marks questions should be approximately of 400 words. Each question is
followed by evaluation scheme. Each Question carries 10 marks 6 X 10=60.
Q1. A statistical survey is a
scientific process of collection and analysis of numerical data. Explain the
stages of statistical survey. Describe the various methods for collecting data
in a statistical survey.
Answer. A statistical survey is a scientific process of
collection and analysis of numerical data. Statistical survey are use to
collect numerical information about units in population. Surveys involve asking
questions to individuals.
Surveys of
human populations are common in government, health, social science and
marketing sectors. Stages of Statistical Survey-
Q2. Analysis of daily wages of
workers in two organizations A and B yielded the following results:
Organizations
A
|
B
|
|
No. of workers
|
10
|
20
|
Average daily wages (Rs)
|
30
|
15
|
Variance
|
25
|
100
|
Obtain the average daily wages and
the standard deviation of wages of all workers in the two organisations taken
together. Which organisation is more equitable in regard to wages?
Answer. (A) Combined Mean:
So, Ź = (10 *
30 + 20 * 15)/(10+20)
(b) Combined
Standard deviation:
Standard
deviation for A, σ1 = (25) ^ ½ = 5.
Standard
deviation for B, σ2 = (100) ^ ½ = 10
Q3. A) State the addition and
multiplication rules of probability giving an example of each case.
B) In a bolt factory machines A, B, C
manufacture 25, 35 and 40 percent of the total output. Of their total output 5,
4 and 2 percent are defective respectively. A bolt is drawn at random and is
found to be defective. What are the probabilities that it was manufactured by
machines A, B and C?
Answer. (a) Addition rule of
probability:
Addition Rule 1: When two events, A and B, are
mutually exclusive, the probability that A or B will occur is the sum of the
probability of each event.
P(A
or B) = P(A) + P(B)
Addition Rule 2: When two events, A and B, are
non-mutually exclusive, the probability that A or B will occur is:
P(A
or B) = P(A) + P(B)
Q4. a. What is a Chi-square test?
Point out its applications. Under what conditions is this test applicable?
b. Discuss the types of measurement
scales with examples.
Answer. (a) A chi-squared test, also referred to as chi-square test
or test, is any statistical hypothesis test in which the sampling distribution
of the test statistic is a chi-squared distribution when the null hypothesis is
true. Also considered a chi-squared test is a test in which this is asymptotically
true, meaning that the sampling distribution (if the null hypothesis is true)
can be made to approximate a chi-squared
Q5. Explain the Components of Time
series.
Answer. A time series is a sequence of data points,
measured typically at successive points in time spaced at uniform time
intervals. Examples of time series are the daily closing value of the Dow Jones
Industrial Average and the annual flow volume of the Nile River at Aswan. Time
series are very frequently plotted via line charts. Time series are used in
statistics, signal processing, pattern recognition, econometrics, mathematical
finance, weather forecasting, earthquake prediction, electroencephalography,
control engineering
Q6. a. What is analysis of variance?
What are the assumptions of the technique?
b. Three samples below have been
obtained from normal populations with equal variances. Test the hypothesis at
5% level that the population means are equal.
A
|
B
|
C
|
8
|
7
|
12
|
10
|
5
|
9
|
7
|
10
|
13
|
14
|
9
|
12
|
11
|
9
|
14
|
[The table value of F at 5% level of
significance for 1 = 2 and 2 = 12 is 3.88]
Answer. (a) Analysis of
Variance (ANOVA) is
a statistical method used to test differences between two or more means. It may
seem odd that the technique is called "Analysis of Variance" rather
than "Analysis of Means." As you will see, the name is appropriate
because inferences about means are made by analyzing variance.
In ANOVA setting, the observed variance in a particular
variable is partitioned into components attributable to different sources of
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