Business Statistics and Research Methods MCQs

Match the items of List-I and List-II and indicate the correct matching of the items.

List-I	List-II
a. $$\frac{{{z^2} \cdot \sigma _p^2}}{{{e^2}}}$$	1. Measurement for Kurtosis
b. $$\frac{{\left| {\overline {{X_1}} - \overline {{X_2}} } \right|}}{{\sqrt {\sigma _p^2\left( {\frac{1}{{{n_1}}} + \frac{1}{{{n_2}}}} \right)} }}$$	2. Calculated value of F ratio
c. $$\frac{{{\mu _4}}}{{\mu _2^2}}$$	3. Statistical approach to find out the size of sample
d. $$\frac{{\sigma _1^2}}{{\sigma _2^2}}$$	4. Calculated z value of mean differences

Match the items of List-I with the items of List-II and indicate the option of correct matching:

List-I	List-II
a. Contingency coefficient for any size of contingency table	1. $$\sqrt {\frac{{N - n}}{{N - 1}}} $$
b. Statistical approach to decide size of a sample	2. $$\frac{{{\sigma _p}}}{{\sqrt n }}$$
c. Finite population multiplier	3. $$\sqrt {\frac{{{x^2}}}{{{x^2} + n}}} $$
d. Standard error of mean	4. $$\frac{{{Z^2}.\sigma _p^2}}{{{e^2}}}$$

With reference to the value of Q₃ which of the following statement is/are correct?
(1) 1.5 of mean $$\left( {\overline X } \right)$$
(2) 75^th percentile
Choose the correct answer from the options give below

Match the following.

List-I (Terms)	List-II (Definitions)
a. Simple regression	1. Process of predicting one variable from another
b. Multiple regression	2. Single variable is used to predict another variable on the assumption of linear relationship between the given variables
c. Simple linear regression analysis	3. Involves two or more independent variables and one dependent variable

The income of 5 persons are as follows

Person	Income per month (Rs.)
Ram	1,500
Shyam	1,700
Mohan	2,000
Aryan	5,000
Krishna	6,000

Types of above series . . . . . . . .

In the application of chi-square,
1. no theoretical frequency should be small since in the derivation of chi-square continuity assumptions are made.
2. the constraint imposed on cell frequencies must be linear.
3. regroup the frequencies whenever some expected frequency was small.
4. the correction is needed, when some cell frequency was small, i.e. less than 5.
Which of the statements given above are correct?

If Σx = 12, Σy = 42, Σx² = 46, Σy² = 542, Σxy = 157 and n = 4, find the correlation coefficient.

Which of the following statement is/are correct?
(1) Statistics deals with aggregate of facts.
(2) All facts numerically expressed are Statistics.
Select the correct answer using the options given below

Match List-I with List-II and select the correct answer:

List-I	List-II
a. Coefficient of determination	1. $${\gamma _{xy}}\frac{{{\sigma _x}}}{{{\sigma _y}}}$$
b. Spearman's rank correlation coefficient	2. $$1 - \frac{{6\sum {{d^2}} }}{{n\left( {{n^2} - 1} \right)}}$$
c. Regression coefficient of $$x$$ on $$y$$ variable	3. $$\frac{{\sum {xy} }}{{n\,{\sigma _x}\,{\sigma _y}}}$$
d. Karl Pearson's formula of calculating $$\gamma $$	4. $${\gamma ^2}$$