IGNOU MCO-03 December 2022 Previous Year Question Paper

Q1.(a) What is a research problem ? In the light of research problem , how are hypothesis framed ? Explain with examples. 10

(b) What are the statistical techniques used to test the hypothesis ? Explain them briefly. [ 2 ]

Q2.(a) What do you mean by range ? Explain with the help of an example. 6

(b) Find the probability of exactly 4 defective tools in a sample of 30 tools chosen at random by a certain tool producing firm by using

(i) Bin omial distribution and

(ii) Poisson distribution. The probability of defects in each tool is given to be 0.02.

Q3.(a) Define a binomial probability distribution and state the conditions under which the binomial probabilty model is appropriate.

(b) Explain the procedure involved in P oisson distribution.

Q4.What do you understand by the term index numbers ? Discuss the uses of index numbers in the context of business and economic activity. 5, 15 [ 3 ]

Q5.Prepare a detailed hypothetical structure of the Research Report.

Q6.Briefly comment on the following : 5×4=20

(a) Random sampling is a part of the sampling technique in which each sample has an equal probability of being chosen.

(b) A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features.

(c) The ANOVA is also appropriate when there is more than one explanatory factor, in which case a multifactor ANOVA may be used.

(d) The independent variable is the variable the experimenter manipulates or changes , and is assumed to have a direct effect on the dependent variable.

(e) Expected value is the fundamental idea in the study of probability distributions.

Q7.Distinguish between any two of the following : 10+10

(a) Z-test and t-test

(b) Comparative and N on-comparative scaling techniques

(c) Type-I and Type-II error

Q8.Write short notes on any four of the following : 4×5=20

(a) Correlation

(b) Price indices

(c) Level of significance

(d) Pie diagram

(e) Skewness okf.kT; esa LukrdksÙkj mikf/ (,e- dkWe-) l=kkar ijh{kk fnlEcj] 2022 ,e-lh-vks--003 % vuqla/ku fof/;k¡ ,oa lkaf[;dh; fo'ys"k.k le; % 3 ?k.Vs vf/dre vad % 100 Hkkfjrk % 70% uksV % fdUgha ik¡p iz'uksa ds mÙkj fyf[k,A lHkh iz'uksa ds vad leku gSaA 1-

(d) vuqla/ku leL;k ls D;k rkRi;Z gS \ vuqla/ku leL;k ds izdk'k esa izkDdYiuk (hypothesis) dk fuekZ.k dSls fd;k tkrk gS \ mnkgj.k lfgr O;k[;k dhft,A 10 ([k) izkDdYiuk ds ijh{k.k ds fy, mi;ksx dh tkus okyh lkaf[;dh; izfof/;k¡ D;k gSa \ la{ksi esa O;k[;k dhft,A 10 2-

(d) lhek (Range) ls vkidk D;k eryc gS \ ,d mnkgj.k dh enn ls le>kb,A 6 ([k) ,d ;a=k fuekZ.k iQeZ }kjk mRikfnr ;a=kksa ls 30 nSo izfrn'kks± esa ls Bhd 4 nks"kiw.kZ ;a=kksa dh izkf;drk fuEu vk/kj ij Kkr dhft, %

(i) f}in caVu ,oa

(ii) IokW;lka caVuA izR;sd ;a=k ds nks"kiw.kZ gksus dh izkf;drk 0-02 gSA 14 3-

(d) f}in izkf; drk caVu (binomial probability distribution) dh ifjHkk"kk nhft, rFkk mu fLFkfr;ksa dk mYys[k dhft, ftuds v arxZr f}in izkf;drk ekWMy dks mi;qDr ekuk tkrk gSA 10 ([k) IokW;lka caVu (Poisson distribution) esa fufgr izfØ;k dh O;k[;k dhft,A 10 4- ^vuqla/ku izjpuk* (vfHkdYi) ls vkidk D;k rkRi;Z gS \ vuqla/ku izjpuk ds fofHkUu ?kVdksa dh foospuk dhft,A 5] 15 5- 'kks/ fjiksVZ dh foLr`r dkYifud lajpuk dks rS;kj dhft,A 20 6- fuEufyf[kr ij la{ksi esa fVIi.kh dhft, % 5×4¾20

(d) jSaMe lSaifyax lSaifyax rduhd dk ,d fgLlk gS ftlesa izR;sd lSaiy dks pqus tkus dh leku laHkkouk gksrh gSA ([k) ,d Vh&VsLV ,d izdkj dk vuqe kukRed vk¡dM+k gS ftldk mi;ksx ;g fu/kZfjr djus ds fy, fd;k tkrk gS fd D;k nks lewgksa ds lk/uksa ds chp egRoiw.kZ varj gS ] tks dqN fo'ks"krkvksa esa lEcfU/r gks ldrs gSaA (x) ANOVA Hkh mi;qDr gS tc ,d ls vf/d O;k[;kRed dkjd gksrs gSa ] ftl fLFkfr esa ,d eYVh,DVj ANOVA dk mi;ksx fd;k tk ldrk gSA (?k) Lora=k pj og pj gS ftls iz;ksxdrkZ gsjiQsj ;k ifjorZu djrk gS ] vkSj ekuk tkrk gS fd fuHkZj pj ij lh/k izHkko iM+rk gSA (³) ewy laHkkO;rk forj.k ds vè;;u esa ekSfyd fopkj gSaA 7- fuEufyf[kr eas ls fdUgha nks esa Hksn dhft, % 10+10

(d) tsM&VsLV vkSj Vh&VsLV ([k) rqyukRed vkSj xSj&rqyukRed Ldsfyax rduhd (x) Vkbi-I vkSj Vkbi-II =kqfV 8- fuEufyf[kr esa ls fdUgha pkj ij y?kq uksV fyf[k;s % 4×5=20

(d) lglEcU/ (Correlation) ([k) dher lwpdkad (x) lkFkZdrk Lrj (?k) o`Ùk vkjs[k (Pie diagram) (³) oS"kE; (Skewness)