Thursday, October 25, 2018

BUSINESS STATISTICS MULTIPLE CHOICE QUESTIONS


Multiple Choice Questions for November’ 2018:
Unit – 1: Average and Dispersion
Q. Calculation of GM, HM, AM from 5,3,3,1,3,3,4,1,0
Q. Define sample and census.
Q. Define pie chart and bar diagram.
Q. What is frequency distribution table?
Q. Which is best measure of dispersion (SD) and best measure of central tendency (Mean)?
Q. Range = H – L
Q. Q2 = 1/2(Q1 + Q3)
Q. SD of two given numbers = 1/2 (H – L)
Q. SD of natural number = square root of (n2- 1)/12
Q. If SD of X is 5 then SD of 2x – 1 and 4x/2 + 1 will be: 10 in each case.
Unit – 2: Correlation and Regression
Q. Range of correlation = +1 to -1.
Q. Increase on prices and selling of products = Negative correlation
Q. Age of husbands and wives = Positive correlation
Q. Intelligence and size of shoe = No correlation
Q. Karl Pearson’s coefficient of correlation measures QUANTITATIVE DATA.
Q. Spearmen’s Rank correlation measures QUALITATIVE DATA.
Q. r is the GM of two regression coefficients.
Q. There is only one line if r = + 1.
Q. Regression lines will be parallel if r = 0.
Q. No of regression lines: 2
Q. Two regression lines intersect at the respective mean of X and Y.
Unit – 3: Index Number
1. Only Fisher’s index number is the ideal index number which satisfied time reversal and factor reversal test.
2. Fisher’s index is the GM of Laspeyre’s and Paasche’s index number.
3. Base year index = 100
4. P01 x P10 = 1 or P0n x Pn0 = 1
5. P01 x Q01 = Value index number
6. Net monthly income of an employee was Rs.800 pm in 1980. The consumer price index number was 160 in 1980. It rises to 200 in 1984. Calculate DA and his wages.
Ans: DA = 40/160*800 = 200 and his wages should be = 200/160*800 = 1000
7. Index number in 2000 is 140 which increase to 200 in 2010. What does it mean?
Ans: It means prices are increased by 60% in 2010 as compared to 2000.
Unit – 4: Time Series Analysis
Q. Examples of irregular variation: Flood, fire, strike, lockout, earthquake, hot wave in winter, rain in desert.
Q. Examples of seasonal variation: sale of woolen clothes during winter, decline in ice-cream sales during winter, demand of TV during international games.
Q. Examples of cyclical variation: Recession, Boom, Depression, Recovery, balancing of demand and supply.
Q. Examples of Trend or secular trend: Increase in demand of two wheeler, decrease on death rate due to advancement of medical science, increase in food production due to increase in population.
Q. Multiplicative model: T.C.S.I and Additive model: T + C + S + I. here T = Secular Trend, C = Cyclical trend, S = Seasonal variation and I = Irregular variation.
Q. Short term forecasting = Seasonal trend and long term forecasting = Secular trend.
Q. Y = TCSI (Multiplicative model) or T + C + S + I (Additive model).

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