✅ 100 Questions with One-Word Answers (MCQ Style — No Options)

SECTION 1: Basics of Statistics (Q1–15)

1. Statistics primarily deals with data.

2. The first step in any statistical investigation is collection.

3. Organizing data in rows and columns is called tabulation.

4. Grouping data into classes is called classification.

5. A table showing frequency of observations is a distribution.

6. The main limitation of statistics is that it deals with averages.

7. Data collected first-hand is called primary.

8. Data collected from published sources is secondary.

9. Numerical facts are called quantitative data.

10. Non-numerical data are called qualitative.

11. The field dealing with data summary is descriptive statistics.

12. The field dealing with inference is inferential statistics.

13. The arrangement of data by time is a series.

14. Raw facts are called data.

15. Classification based on attributes is qualitative.

SECTION 2: Sampling Techniques (Q16–30)

16. Sampling based on equal chance is random.

17. Selecting samples at fixed intervals is systematic.

18. Dividing population into strata gives stratified sampling.

19. Population divided into clusters uses cluster sampling.

20. A part of population studied is a sample.

21. A complete count is a census.

22. Sampling error decreases with larger size.

23. A sample drawn with replacement is unrestricted.

24. The curve followed by large samples is normal.

25. CLT stands for theorem.

26. Parameter belongs to population.

27. Statistic belongs to sample.

28. Finite population correction is a multiplier.

29. Sampling distribution of mean tends to normal.

30. The method ensuring no bias is randomisation.

SECTION 3: Measures of Central Tendency (Q31–45)

31. The most common average is mean.

32. The middle value is median.

33. The most frequent value is mode.

34. The product-based average is geometric.

35. Reciprocal-based average is harmonic.

36. The simplest measure of dispersion is range.

37. Half of IQR is quartile deviation.

38. Square-root of variance is SD.

39. Variance is square of SD.

40. Mean with weights is weighted mean.

41. Combined mean uses weighted formula.

42. Dispersion relative measure is CV.

43. Lack of symmetry is skewness.

44. Flatness of distribution is kurtosis.

45. A perfectly symmetrical distribution has zero skewness.

SECTION 4: Correlation & Regression (Q46–60)

46. Graphical tool for correlation is scatter.

47. Relationship between variables is correlation.

48. Regression estimates prediction.

49. Karl Pearson coefficient ranges between one (±1).

50. Best-fit line is regression line.

51. Error of prediction is residual.

52. Square of correlation is R².

53. Slope in regression is called beta.

54. Regression minimizing squared errors is OLS.

55. Standard error of estimate measures accuracy.

56. Positive correlation moves upward.

57. Negative correlation moves downward.

58. Correlation of independent variables is zero.

59. Prediction of Y from X uses regression.

60. Multiple regression uses several predictors.

SECTION 5: Time Series (Q61–75)

61. Long-term movement in time series is trend.

62. Regular periodic movement is seasonal.

63. Wave-like movement is cyclical.

64. Unpredictable variations are irregular.

65. Prediction using past data is forecasting.

66. Trend measured via straight line is linear.

67. Data arranged chronologically is time series.

68. Ratio-to-trend method finds seasonal index.

69. Moving average smoothens fluctuations.

70. Graph showing trend is line graph.

71. Seasonal index above 100 means above average.

72. Seasonal index below 100 means below average.

73. Components of time series include trend.

74. When trend is removed, residual is irregular.

75. Trend measured by least squares is LSM.

SECTION 6: Probability & Distributions (Q76–90)

76. Probability values lie between one (0–1).

77. P(A|B) denotes conditional probability.

78. Variable with numeric outcomes is random.

79. Probability distribution of discrete variable is PMF.

80. Probability distribution of continuous variable is PDF.

81. Expected value is mean.

82. Spread of distribution is variance.

83. Binomial distribution has two outcomes.

84. Poisson distribution describes rare events.

85. Normal curve is bell shaped.

86. Credit risk uses concept of default.

87. Tail-risk measure is VaR.

88. Z-score relates to normal distribution.

89. Option pricing uses Black-Scholes.

90. Area under normal curve is one.

SECTION 7: Estimation (Q91–95)

91. A single value estimate is point.

92. Range estimate is interval.

93. Parameter guessed from sample is estimator.

94. Interval estimate uses confidence.

95. Large sample estimate uses z value.

SECTION 8: Linear Programming & Simulation (Q96–100)

96. LP graphical method applies in two variables.

97. Feasible region is always convex.

98. LP optimum lies at corner point.

99. Simplex method is iterative.

100. Simulation imitates reality.

✅ CAIIB – Advanced Bank Management – Module A (Statistics)

100 Topic-wise MCQs with Answers (No options)

📌 TOPIC 1 — BASICS OF STATISTICS (Q1–15)

1. The science of collecting and analyzing data is called Statistics.

2. Data collected first-hand is known as Primary.

3. Data arranged in rows and columns is called Tabulation.

4. Grouping data on the basis of a characteristic is Classification.

5. Numerical data is known as Quantitative.

6. A table that displays frequency of items is Distribution.

7. Information collected from journals is Secondary.

8. Data arranged by time is Chronological.

9. The raw facts collected are called Data.

10. A unit on which observations are taken is a Variable.

11. Arrangement by size is called Array.

12. No. of observations constitutes Frequency.

13. A list of items under similar groups is Class.

14. Highest and lowest values difference is Range.

15. A graphic presentation of classes is a Histogram.

📌 TOPIC 2 — SAMPLING TECHNIQUES (Q16–30)

16. A part of population used for study is a Sample.

17. A complete enumeration is a Census.

18. Equal chance of selection is Random.

19. Dividing population into strata is Stratified.

20. Selecting the kth element is Systematic.

21. Random groups selected as units are Cluster.

22. Sampling error reduces with larger Size.

23. A characteristic of population is a Parameter.

24. A characteristic of sample is a Statistic.

25. The theorem supporting normality in large samples is CLT.

26. Sampling distribution of mean tends to Normal.

27. A list of population units is Frame.

28. Bias-free selection is Randomisation.

29. FPC stands for Correction.

30. Sample mean is an Estimator.

📌 TOPIC 3 — CENTRAL TENDENCY, DISPERSION, SKEWNESS (Q31–50)

31. Sum of values divided by count gives Mean.

32. Middle-most value is Median.

33. Most frequent value is Mode.

34. The product-based average is Geometric.

35. Reciprocal average is Harmonic.

36. The square root of variance is SD.

37. Variation relative to mean is CV.

38. Half of IQR is Quartile deviation.

39. Measure of flatness is Kurtosis.

40. Lack of symmetry is Skewness.

41. Symmetrical distribution has Zero skewness.

42. Extreme values affect Mean.

43. Median is best for Skewed data.

44. Dispersion measured by max-min is Range.

45. Value dividing data in 4 parts is Quartile.

46. Mean of means (pooled) is Combined mean.

47. Squared SD is Variance.

48. Mean unaffected by extreme value is Median.

49. Positive skew has a long Right tail.

50. Negative skew has a long Left tail.

📌 TOPIC 4 — CORRELATION & REGRESSION (Q51–70)

51. Graph showing relationship is Scatter.

52. Relationship between two variables is Correlation.

53. Prediction model is Regression.

54. Perfect correlation equals One.

55. Regression minimizing errors is OLS.

56. Difference between predicted and actual is Residual.

57. Regression constant is Intercept.

58. Regression slope is Beta.

59. Square of correlation is R².

60. A correlation of zero means None.

61. Predicting Y from X uses Regression.

62. Correlation measured by Karl Pearson is Coefficient.

63. Correlation for rank data is Spearman.

64. Regression line represents Trend.

65. Closeness of fit is measured by R².

66. Multiple variables prediction uses Multiple regression.

67. Regression line is of type Linear.

68. Positive correlation moves Upward.

69. Negative correlation moves Downward.

70. Standard error of estimate indicates Accuracy.

📌 TOPIC 5 — TIME SERIES (Q71–85)

71. Long-term movement is Trend.

72. Short-term periodic movement is Seasonal.

73. Wave-like movements are Cyclical.

74. Unpredictable variations are Irregular.

75. Smoothing is done by Moving average.

76. Removing seasonal influence gives Deseasonalised data.

77. Time-related data is Chronological.

78. Ratio-to-trend method finds Index.

79. Forecasting future is Projection.

80. Seasonal index above 100 means High.

81. Seasonal index below 100 means Low.

82. Least squares method fits Trend.

83. Trend line based on slope is Linear.

84. Periodic pattern is Seasonality.

85. Trend estimation uses LSM.

📌 TOPIC 6 — PROBABILITY & DISTRIBUTIONS (Q86–100)

86. Probability ranges between Zero and One (answer: One).

87. P(A|B) indicates Conditional.

88. A variable with random outcomes is Random.

89. Probability mass function is PMF.

90. Continuous distribution function is PDF.

91. Expected value is Mean.

92. Binomial distribution has Two outcomes.

93. Rare event distribution is Poisson.

94. Bell-shaped curve is Normal.

95. Area under normal curve is One.

96. Tail-event risk is VaR.

97. Credit risk mostly depends on Default.

98. Probability of complement is Residual.

99. Option valuation uses Black-Scholes.

100. CLT leads sample mean to become Normal.