BBA 7th Term Test

8/11/2019 BBA 7th Term Test

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A

Statistical Inference for Management

BBA (H) 7thTerm

Test I & II Total Marks: 16

Name: !lass "# $%"#

Note: Attemt all 'estions

1) Differentiate between Experiment, outcome, and sets.

2) Clarify the difference between Sample Point and Eent, if any

!) Some of the "ale and #emale wor$ers at a lar%e plant hae a hi%h school education.

Set & consist of all male wor$ers, Set ' is female wor$ers, Set C is those with a hi%h

school education, Set D is those without a hi%h school education. (dentify the eenta. Collectiely Exhaustie w.r.t %ender.

*) Define +andom ariable with the help of example.

) -ie 'usiness examples of 'inomial distribution.

) /hat is wron% with followin% statement0

a. (f two coins are tossed, there are ! possible outcomes, 2 heads 1 tail, one head

and two tails. ere the probability for each of these outcomes is 1!.

3) /hen to use Poisson distribution0

4) /hat is the alternate name of t5distribution0

6) /hy we always use to ma$e decision on the basis of 7ull hypothesis0

18) /hat do you mean by 9otal ariation, mention its types0

11) & random sample of si:e n is drawn from a 7ormal population with mean and

ariance un$nown.

a. (f n;2, Sample mean;! and s;2 what is t0

12) Differentiate between C.( and


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1) ow to calculate probability in classical approach0

2) Define Exhaustie eent with the help of appropriate paradi%m



school education, Set D is those without a hi%h school education. (dentify the eent

a. (f !88 of the 1888 wor$ers are male, what is the probability of a wor$er is

female, P ?#).

*) Differentiate between discrete and continuous random ariable.

) /hich parameters are obli%atory for the application of 'inomial distribution0

) /hat is wron% with followin% statement0

a. 9he probabilities that a certain truc$ drier would hae 7o, one, two or more

accidents durin% the year are 8.66, 8.8! and 8.86.

3) /rite down the characteristics of 7ormal distribution.4) Define de%ree of freedom.

6) "ention the difference between 7ull and alternate hypothesis.

18) /rite down the alternate name of @ne /ay and 9wo /ay &7@A&.


ariance un$nown.

a. (f n;6, Sample "ean ;2 and t;52, what is s0

12) #or which purpose we use #5distribution0

1!) Define Aariance +atio.

1*) /hy we use different distribution test0

1) ow we can say that B ;101) Define sufficient estimator

13) 9est o 1F 2, if samples of 188 produce means of 2.! and !.1 with standard

deiations of 8.2 and 8.!1, set alpha 1G.

14) Define Conditional Probability

Arentice Signatre>>>>>>>>>>>>>>>>>>>>>>>>>>>

!


BBA (H) 7thTerm

Test I & II Total Marks:16

Name: !lass "# $%"#


1) Enlist three business examples in case of probability.

2) Define mutually exclusie eents with the help of example.


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a. /hat role did the rule of complementary plays0

*) 'riefly define Probability distribution.) /hat are the parameters of 'inomial distribution0

) ow we can differentiate between 'inomial and Poisson distribution0

3) /ho %ae the concept of t5distribution0 /hen and where0

4) (f a sample is ta$en in which nH!8 what problem mi%ht we hae in wor$in% with it0

6) /hat do you mean by the word I9reatmentI0

18) Draw the %eneral form of &7@A& table.


ariance un$nown.

a. (f n;2, s;18, and t;2, what is sample mean0

12) &lternatiely what # distribution is $nown as01!) Define Statistical hypothesis.

1*) /hat type ( and type (( errors indicate0

1) /hen we should use one tailed and two tailed test0

1) Define unbiased estimator.

13) Paired Samples of si:es 2 reported a mean difference of *.2 and standard deiation

of the difference of 21.. 9est for the e=uality of means at G leel.

14) Differentiate between Simple and Composite hypothesis.



BBA (H) 7thTerm


Name: !lass "# $%"#


1) /hich eents are $nown as Complementary eents0

2) Define e=ually li$ely eents with the help of suitable example.

!) Differentiate between 9wo +ules of Probability.

*) /ho %ae the concept of 'inomial distribution and when0

) 9en percent of computer dis$s produced by a new process are defectie. (f there are

28 dis$s in a box. ow many you expect to be defectie0

) /hat is the probability of throwin% 3 or 11 with two dice0

3) /hy a distribution is $nown as t5distribution0

4) 7ame the properties of %ood point estimator.6) /hen is recommended to use &7@A&0

18) ow to calculate de%ree of freedom in &7@A&0


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ariance un$nown.

a. (f s;1, sample mean;1*, and t;!, what is n0

12) /hat are the assumptions of #5distribution0

1!) /hat do you mean by reJection of hypothesis0

1*) /hen we cannot use 'inomial distribution0 -ie example if any

1) Clarify the difference between @ne /ay and 9wo /ay &7@A&

1) Define Consistent estimator.

13) Define the 9erm ICorrection #actorI

14) Explain clearly why a null hypothesis of o K18 re=uires a ri%ht tailed test, while a

null hypothesis of o F18 re=uires a left tailed test.


$


BBA (H) 7thTerm


Name: !lass "# $%"#


1) Define Efficient Estimator.

2) Some of the "ale and #emale wor$ers at a lar%e plant hae a hi%h school education.



a. "utually Exclusie

!) Clarify the difference between permutation and combination*) Enlist the properties of 'inomial distribution.

) /hat is the &ssumptions of Poisson distribution0

) Specify the parameters of 'inomial and Poisson distributions.

3) /hich condition is the least important for the application of t5distribution0

4) Define critical re%ion.

6) /hy we use #5distribution in the testin% of population means0

18)ow to calculate de%ree of freedom when both populations are un$nown but not

identical0

11) /rite down the &ssumptions of t5distribution.

12) /hat is the ran%e of #5distribution0

1!) /hat do you mean by acceptance of hypothesis0

1*) Define and enlist the types of Statistical inference.

1) /hy can we neer accept the null as true0

1) /here the application of &7@A& is in business0


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13) Define multiple way classification in &7@A&.

14) & truc$in% company finds that !8 percent of its shipments arrie late. (f ei%ht

shipments are scheduled what is the probability that

a. 9hree will arrie late.

b. 9hree or more will arrie late


A

B*SIN$SS STATISTI!S

BBA (H) +r,Term


Name: !lass "# $%"#


1) Differentiate between Statistic and Statistics.

2) /hat do you mean by Dichotomous and "ultinomial ariable0

!) Define #re=uency0

*) Specify that what is mid point0

) /hat is the difference between


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3.1G, 3.!G, 3.8G, .6G, .G, .6G, .G, 3.!G, .4G

a. Calculate and interpret, the "ean, "edian, -.", and ."

B

B*SIN$SS STATISTI!S

BBA (H) +r,Term


Name: !lass "# $%"#


1) ow Cowden defined Statistics0

2) Enlist the techni=ues which are used for the collection of primary data0

!) /hat is fre=uency distribution0

*) /rite down the rule which is used for decidin% the 7umber of classes

) /hy we need %raphical representation0

) /hen we use three dimensional dia%rams0

3) /hy we need to calculate measure of location0

4) /here we use -."0

6) 9here is 7o mode in the data, what does it mean0

18) /hat is the alternate name of "easure of Dispersion0

11) /hen we cannot Calculate &." by usin% Step Deiation method0

12) /hat is the ran%e of 7ormal distribution in case of $urtosis0

1!) /hat are the basic functions of re%ression lines0

1*) -ie real life example of secular trend.

1) 7ame the techni=ues which are used for measurin% Secular 9rend.

1) Define 'ase period0

13) (nterest rates fell in early 1663, a sample of mort%a%e rates for 1 years, mort%a%e at

local lendin% institutions in Peoria, (


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3.1G, 3.!G, 3.8G, .6G, .G, .6G, .G, 3.!G, .4G

a. &re the Data s$ewed left, or ri%ht, or are they normally distributed0 calculate

the pearsonian coefficient as a measure of s$ewness

!

B*SIN$SS STATISTI!S

BBA (H) +r,Term


Name: !lass "# $%"#


1) Discuss the applications of Statistics in 'usiness.

2) /hat do you understand from uniariate and multiariate0

!) "ention the purpose of fre=uency distribution0

*) ow we can decide the si:e of class interal durin% the construction of fre=uency

distribution0

) (n how many %roups isual display is diided, namely

) Specify the difference between carto%ram and picto%ram

3) Differentiate between measure of position and measure of location.

4) /here we use wei%hted mean0

6) Differentiate between bimodal and multimodal

18) /hat does measure of dispersion measures0

11) /hy we use coefficient of ariation0

12) Define co5ariance0

1!) 9ell the difference between simple and biariate re%ression

1*) /hat is the basic concept of seasonal ariation0

1) "ention the merits of #ree hand cure.

1) Define current period0

13) & data set contains 188 obserationsM the lar%est is !1 and the smallest is .


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a. ow many classes should the fre=uency table hae0

b. /hat is the class interal0

c. /hat are the bounds and mid points of each class0

B*SIN$SS STATISTI!S

BBA (H) +r,Term


Name: !lass "# $%"#


1) /hat are the main areas of 'usiness Statistics0

2) "ention the charactertics of Data.

!) Define class limit with the help of example.

*) /hat is tally0

) 9ell the basic difference between %raph and dia%ram0

) /hat is the alternate name of ori:ontal &xis0

3) "ention the basic obJecties of &era%e0

4) /hy median is $nown as positional aera%e0

6) Enlist the techni=ues which are used for calculatin% mode0

18) /hat is the difference between absolute and relatie measure of dispersion0

11) Define moments0

12) /hat /.(.Lin% said about correlation0

1!) Define time series0

1*) #or which purpose we use seasonal ariation0

1) /rite down the basic principle of moin% aera%e method

1) Differentiate between Simple and composite index no

13) 9he no of daily telephone calls comin% into a switch board at a busy office are shown

below. Calculate ! period moin% aera%es.


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Day 1 2 ! * 3 4 6 18 11

Calls *8 !3 * !2 *2 * !6 *4 *1 ! !4

$

B*SIN$SS STATISTI!S

BBA (H) +r,Term


Name: !lass "# $%"#


1) Differentiate between Descriptie and (nferential statistics0

2) Define classification0

!) /hat is class boundary0

*) 'riefly define cumulatie fre=uency0

) /hich rule is the most important for the construction of dia%ram0

) /hat is the purpose of calculatin% proportional fre=uency0

3) /here we use &."0

4) /rite down the three benefits of median

6) /hy mode is not affected by extreme lar%e or extreme small alues0

18) ow we can calculate coefficient of ran%e0

11) /hat do you understand by moments about mean and about proisional mean0

12) /hat is the difference between correlation and coefficient of correlation0

1!) Define &nalysis of time series0

1*) /hat do you mean by cyclical fluctuations0

1) /hat do you mean by period of moin% aera%e0

1) /hat do you understand from wei%hted and unwei%hted index no0

13) Calculate the coefficient of correlation between the alues of N and O %ien

N 34 46 63 6 6 36 4 1


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O 12 1!3 1 112 183 1! 12! 184

-

B*SIN$SS STATISTI!S

BBA (H) +r,Term


Name: !lass "# $%"#


1) /hat are the basic cons of 'usiness Statistics0

2) Define the term I9abulationI0

!) /hat do you mean by class interal0

*) /hat is relatie fre=uency and how to calculate it0

) Clarify the difference between simple bar and multiple bar dia%ram.

) /hat is the alternate name of fre=uency poly%on0

3) /hen we use median0

4) /hy sortin% of data is important in median0

6) ow -." %ies more importance to data0

18) Define .D0

11) (n moments when we calculate arbitrary means0

12) 7arrate the difference between positie and ne%atie correlation.

1!) "ention in blac$ Q white the purpose of &nalysis of time series.

1*) /hat is the alternate name of irre%ular ariation other than random ariation0

1) /rite down the Demerits of "oin% &era%e method.

1) /hy #isherRs index no is $nown as (deal index no0

13) /hat can you say of the s$ewness in each of the followin% cases0

a. 9he median is *6.21 while two =uartiles are !3.1 and 1.23


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b. "ean; 1*8! and "ode; 1*43

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BBA 7th Term Test