Skip to main content

MCQ'S based on Basic Statistics (For B. Com. II Business Statistics)

 

 (MCQ Based on Probability, Index Number, Time Series  and Statistical Quality Control Sem - IV)                                                          

1.The control chart were developed by ……       

A) Karl Pearson

B) R.A. fisher

C) W.A. Shewhart

D) B. Benjamin

 

2.the mean = 4 and variance = 2 for binomial r.v. x then value of n is…..

A) 7

B) 10

C) 8

D)9

 

3.the mean = 3 and variance = 2 for binomial r.v. x then value of n is…..

A) 7

B) 10

C) 8

D)9

4. If sample space S={a,b,c}, P(a) = 0.6 and P(b) = 0.3 then P(c)=…..

A)0.6

B)0.3

C)0.5

D)0.1

 

5 Index number is called

A) geometer

B)barometer

C)thermometer

D)centimetre

 

6.  Index number for the base period is always takes as

A)200

B)50

C)100

D)1

 

 

7. Index number are called as….

A)economic thermometer

B)economic barometer

C)social barometer

D)thermometer

 

8. Seasonal variation are….

A)sudden variation

B)short term variation

C)long term variation

D)none of them

 

9. control chart consist of

A)3 control lines

B) 2 control line

C)central line

D)non of them

10. A time series has .....components.

A)one

B)two

C)three

D)four

 

11. which of the following is a variable chart?

A)x bar chart

B)R chart

C)p chart

D)both A and B

 

12. If Laspeyre’s index = 100, Paasche’s index =169 then fisher index is equal to .

A)1330

B)16900

C)130

D)280

13. If Laspeyre’s index = 100, Paasche’s index =144 then fisher index is equal to .

A)122

B)244

C)120

D)280

 

 

14. for standard normal variate the mean and variance are

A)mean = 0 variance = 1

C)mean = 0 variance = 0

B)mean =1 variance = 1

D)mean =1 variance = 0

15. If Laspeyre’s index = 100, Paasche’s index =169 then fisher index is equal to .

A)1330

B)16900

C)130

D)280

 

16.Tickets are numbered from 1 to 50. One ticket is drawn at random, then probability that drawn ticket has a number 7 or it is multiple is ..

A)1/20

B)1/5

C)1/7

D)7/50

 

17.which of the following is an attribute control chart?

A)X bar chart

B)np-chart

C)R-chart

D all the above

 

18. Prosperity, recession, depression and recovery in a business is an example of ..

A)irregular variation

B)seasonal variation

C)cyclical variation

D)secular trend

 

19. Probability of certain event is …..

A)0

B)1

C)0.5

D)-1

20. Prosperity, recession, depression and recovery in a business is an example of ..

A)irregular variation

B)seasonal variation

C)cyclical variation

D)secular trend

 

 (MCQ Based on Measure of central tendency, Dispersion, Correlation and Regression and basic of Statistics sem- III)

 

1. Number of students in a class is an example of --------variable.             

 

    A) Discrete

B) continuous

C) random

D) both A & B

 

 

 

 

 

 

 

2. Method of collecting data from every member of population is called as ….

 

 

    A)Sampling

B)Census

C)SRSWR

D)SRSWOR

 

 

 

3. Data consist with smallest observation 10 occurs 20 times and largest observation 70 occurs 5 time then range of this data is….

 

 

    A)80

B)60

C)15

D)5

 

 

4. Karl Pearson’s correlation coefficient is always lies between……

 

    A) (0 to 1)

B) (-1 to 1)

C) (-1 to 0)

D) (-0.8 to 0.8)

 

5. The mean of data 24, 23, 21, 19, 17, 16 is ….

 

    A) 16

B) 20

C)18

D)22

 

 

6 If we collect blood group of person’s then it is …..

 

  A)Quantitative data

B)Both A & B

C)Qualitative data

D)none of these

 

7. Which sampling is based on equal probability

 

    A) Simple random sampling   

B) Stratified random sampling

 

    C) Systematic sampling 

D) Probability sampling

 

8. If n= 20 and sum of square of deviation of observation taken from mean is 80 then S.D. is ….

 

    A)4

B)2

C)16

D)5

 

9. The mean of data 15, 20, 25, 18, 24, 28, 10 is ….

 

  A) 16

B) 20

C)18

D)22

 

10. If the smallest value in a set is 82 and its range is 4, the largest value is ---

 

    A) 7       

B) 9  

C) 86

D) 6

 

 

 

 

 

 

11. The equation of regression line y on x is Y= 2+0.5X and if we know Value of     X = 4 then estimate value  of Y is ….

 

    A) 2

B)4

C) 1

D)cannot find

 

12. Advertisement and sale have ……

 

  A)Positive correlation

B)negative correlation

 

  C)both A and B

D)no correlation

 

13. Which average is said to be the best average?

 

    A) Mean

B) Median

C)Mode

D) none of them

 

14. The concept of rank correlation was given by:

 

    A)Galton

B)Spearman

C)Karl Pearson

D)Mood

 

15. Which of the following is absolute measure?

 

  A)coefficient of Q.D.

B) Mean

C) coefficient of S.D.

D)Range

 

16. Median of the values 20, 25, 23, 30, 37 is --

 

    A)23

B)25

C)20

D)37

 

 

17…… Divide the data into two equal parts.

 

    A)Mean

B)Median

C)Mode

D) none of these

 

18. if two regression coefficient byx =4 and bxy = (1/16) then correlation coefficient  r is ….

 

  A)-1/2

B)1/4

C)1/2

D)-1/4

 

19. Variance of 5 observations 20, 20, 20, 20, 20 is ----

 

    A)20

B)100

C)5

D)0

 

 

20.Which of the following is advantage of sampling method over census method?

 

    A)more time

B)less cost

C)less Reliable

D)All the above

 

21. Variance is ….. of S.D.

 

  A)Square

B)square root

C)log

D)none of these

 

 

 

 

 

 

22. The estimate of value of X for given Value of Y is obtained by using

 

    A)line of regression Y on X

B)Correlation between X and Y

 

    C) Line of regression X on Y

D) none of them

 

23. Which of the following is a discrete variable?

 

  A)length

B)width

C)age

D)no. of students

 

24.If mean = median = 20 then by empirical relation value of mode is …

 

  A)5

B)10

C)15

D)20

 

 

Comments

Post a Comment

Popular posts from this blog

Basic Concepts of Probability and Binomial Distribution

 Probability:  Basic concepts of Probability:  Probability is a way to measure hoe likely something is to happen. Probability is number between 0 and 1, where probability is 0 means is not happen at all and probability is 1 means it will be definitely happen, e.g. if we tossed coin there is a 50% chance to get head and 50% chance to get tail, it can be represented in probability as 0.5 for each outcome to get head and tail. Probability is used to help us taking decision and predicting the likelihood of the event in many areas, that are science, finance and Statistics.  Now we learn the some basic concepts that used in Probability:  i) Random Experiment OR Trail: A Random Experiment is an process that get one or more possible outcomes. examples of random experiment include tossing a coin, rolling a die, drawing  a card from pack of card etc. using this we specify the possible outcomes known as sample pace.  ii)Outcome: An outcome is a result of experiment. an outcome is one of the pos
1 comment
Read more

Statistical Inference II Notes

Likelihood Ratio Test 
Post a Comment
Read more

Measures of Central Tendency :Mean, Median and Mode

Changing Color Blog Name  Measures of Central Tendency  I. Introduction. II. Requirements of good measures. III. Mean Definition. IV . Properties  V. Merits and Demerits. VI. Examples VII.  Weighted Arithmetic Mean VIII. Median IX. Quartiles I. Introduction Everybody is familiar with the word Average. and everybody are used the word average in daily life as, average marks, average of bike, average speed etc. In real life the average is used to represent the whole data, or it is a single figure is represent the whole data. the average value is lies around the centre of the data. consider the example if we are interested to measure the height of the all student and remember the heights of all student, in that case there are 2700 students then it is not possible to remember the all 2700 students height so we find out the one value that represent the height of the all 2700 students in college. therefore the single value represent the whole data and
1 comment
Read more

Time Series

 Time series  Introduction:-         We see the many variables are changes over period of time that are population (I.e. population are changes over time means population increase day by day), monthly demand of commodity, food production, agriculture production increases and that can be observed over period of times known as time series. Time series is defined as a set of observation arranged according to time is called time series. Or a time Series is a set of statistical observation arnging chronological order. ( Chronological order means it is arrangements of variable according to time) and it gives information about variable.  Also we draw the graph of time series to see the behaviour of variable over time. It can be used of forecasting. The analysis of time series is helpful to economist, business men, also for scientist etc. Because it used to forecasting the future, observing the past behaviour of that variable or items. Also planning for future, here time series use past data h
1 comment
Read more

Sequential Analysis: (SPRT)

  Sequential Analysis: We seen that in NP theory of testing hypothesis or in the parametric test n is the sample size and is regarded as fixed and the value of α fixed , we minimize the value of β.  But in the sequential analysis theory invented by A Wald in sequential analysis n is the sample number is not fixed but the both values α and β are fixed as constant. Sequential Probability Ratio Test: (SPRT):
Post a Comment
Read more

Classification, Tabulation, Frequency Distribution, Diagrams & Graphical Presentation.

Business Statistics I    Classification, Tabulation, Frequency Distribution ,  Diagrams & Graphical Presentation. In this section we study the following point : i. Classification and it types. ii. Tabulation. iii. Frequency and Frequency Distribution. iv. Some important concepts. v. Diagrams & Graphical Presentation   I. Classification and it's types:        Classification:- The process of arranging data into different classes or groups according to their common  characteristics is called classification. e.g. we dividing students into age, gender and religion. It is a classification of students into age, gender and religion.  Or  Classification is a method used to categorize data into different groups based on the values of specific variable.  The purpose of classification is to condenses the data, simplifies complexities, it useful to comparison and helps to analysis. The following are some criteria to classify the data into groups.        i. Quantitative Classification :-
Post a Comment
Read more

Measures of Dispersion : Range , Quartile Deviation, Standard Deviation and Variance.

Measures of Dispersion :  I.  Introduction. II. Requirements of good measures. III. Uses of Measures of Dispersion. IV.  Methods Of Studying Dispersion:     i.  Absolute Measures of Dispersions :             i. Range (R)          ii. Quartile Deviation (Q.D.)          iii. Mean Deviation (M.D.)         iv. Standard Deviation (S. D.)         v. Variance    ii.   Relative Measures of Dispersions :              i. Coefficient of Range          ii. Coefficient of Quartile Deviation (Q.D.)          iii. Coefficient of Mean Deviation (M.D.)         iv. Coefficient of Standard Deviation (S. D.)         v. Coefficient of Variation (C.V.)                                                                                                                    I.  Introduction. We have the various measures of central tendency, like Mean, Median & Mode,  it is a single figure that represent the whole data. Now we are interested to study this figure(i.e. measures of central tendency) is proper represe
Post a Comment
Read more

Business Statistics Notes ( Meaning, Scope, Limitations of statistics and sampling Methods)

  Business Statistics Paper I Notes. Welcome to our comprehensive collection of notes for the Business Statistics!  my aim is to provided you  with the knowledge you need as you begin your journey to comprehend the essential ideas of this subject. Statistics is a science of collecting, Presenting, analyzing, interpreting data to make informed business decisions. It forms the backbone of modern-day business practices, guiding organizations in optimizing processes, identifying trends, and predicting outcomes. I will explore several important topics through these notes, such as: 1. Introduction to Statistics. :  meaning definition and scope of  Statistics. 2. Data collection methods. 3. Sampling techniques. 4. Measures of  central tendency : Mean, Median, Mode. 5. Measures of Dispersion : Relative and Absolute Measures of dispersion,  Range, Q.D., Standard deviation, Variance. coefficient of variation.  6.Analysis of bivariate data: Correlation, Regression.  These notes will serve as you
Post a Comment
Read more

Statistical Quality Control

 Statistical Quality Control  Statistical quality control (S. Q. C.) is a branch of Statistics it deals with the application of statistical methods to control and improve that quality of product. In this use statistical methods of sampling and test of significance to monitoring and controlling than quality of product during the production process.  The most important word in statistical Quality control is quality  The quality of product is the most important property while purchasing that product the product fulfill or meets the requirements and required specification we say it have good quality or quality product other wise not quality. Quality Control is the powerful technique to diagnosis the lack of quality in material, process of production.  Causes of variation:   When the product are produced in large scale there are variation in the size or composition the variation is inherent and inevitable in the quality of product these variation are classified into two causes.  1) chan
Post a Comment
Read more