Mathematics · Quantitative Aptitude
Statistics and Dispersion
559 Questions
Statistics and dispersion involve the calculation of mean, standard deviation, variance, and coefficient of variation for data sets. These questions also cover probability distributions and cumulative frequency analysis. Such quantitative aptitude topics are heavily featured in banking and SSC examinations.
Standard deviationNormal distributionMean calculationCumulative frequencyCoefficient of variation
Statistics and Dispersion Questions
What is the purpose of a scatter plot?
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To show the distribution of a variable across a region
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To show the relationship between two variables
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To show the movement of people or goods
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To show the physical features of a region
B
Correct answer
Explanation
Scatter plots are used to show the relationship between two variables by plotting the values of one variable on the x-axis and the values of the other variable on the y-axis.
What is the purpose of a line graph?
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To show the distribution of a variable across a region
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To show the relationship between two variables
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To show the movement of people or goods
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To show the physical features of a region
C
Correct answer
Explanation
Line graphs are used to show the movement of people or goods over time by plotting the values of the variable on the y-axis and the time on the x-axis.
Which of the following is a continuous data type?
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Age
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Gender
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Height
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Occupation
C
Correct answer
Explanation
Continuous data types can take on any value within a range, such as height or weight.
Which of the following is a discrete data type?
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Age
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Gender
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Height
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Occupation
B
Correct answer
Explanation
Discrete data types can only take on specific values, such as gender or occupation.
Which of the following mathematics journals is published by the Institute of Mathematical Statistics?
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The Annals of Statistics
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The Annals of Probability
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The Journal of the American Statistical Association
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Statistical Science
A
Correct answer
Explanation
The Annals of Statistics is published by the Institute of Mathematical Statistics.
A company claims that their product has a mean lifespan of 1000 hours. A sample of 50 products is tested and the sample mean lifespan is found to be 950 hours. If the population standard deviation is known to be 100 hours, what is the p-value for the hypothesis test that the population mean lifespan is equal to 1000 hours?
B
Correct answer
Explanation
The p-value is the probability of obtaining a sample mean lifespan as extreme as or more extreme than the observed sample mean, assuming that the population mean lifespan is equal to 1000 hours. Using a z-test, the p-value is calculated as P(Z < -2.5) = 0.01.
A company uses a control chart to monitor the quality of their products. The control limits are set at 3 standard deviations above and below the mean. If the sample mean is 100 and the sample standard deviation is 10, what are the control limits?
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(70, 130)
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(80, 120)
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(90, 110)
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(100, 140)
A
Correct answer
Explanation
The control limits are calculated as the mean plus or minus 3 standard deviations. Therefore, the control limits are 100 +/- 3 * 10 = (70, 130).
A company claims that their product has a mean lifespan of 500 hours. A sample of 100 products is tested and the sample mean lifespan is found to be 480 hours. If the population standard deviation is known to be 50 hours, what is the p-value for the hypothesis test that the population mean lifespan is equal to 500 hours?
B
Correct answer
Explanation
The p-value is the probability of obtaining a sample mean lifespan as extreme as or more extreme than the observed sample mean, assuming that the population mean lifespan is equal to 500 hours. Using a z-test, the p-value is calculated as P(Z < -2) = 0.05.
A company uses a control chart to monitor the quality of their products. The control limits are set at 2 standard deviations above and below the mean. If the sample mean is 100 and the sample standard deviation is 10, what are the control limits?
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(80, 120)
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(90, 110)
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(100, 140)
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(110, 130)
A
Correct answer
Explanation
The control limits are calculated as the mean plus or minus 2 standard deviations. Therefore, the control limits are 100 +/- 2 * 10 = (80, 120).
A company claims that their product has a mean lifespan of 1000 hours. A sample of 50 products is tested and the sample mean lifespan is found to be 900 hours. If the population standard deviation is known to be 100 hours, what is the p-value for the hypothesis test that the population mean lifespan is equal to 1000 hours?
A
Correct answer
Explanation
The p-value is the probability of obtaining a sample mean lifespan as extreme as or more extreme than the observed sample mean, assuming that the population mean lifespan is equal to 1000 hours. Using a z-test, the p-value is calculated as P(Z < -3) = 0.01.
A company uses a control chart to monitor the quality of their products. The control limits are set at 4 standard deviations above and below the mean. If the sample mean is 100 and the sample standard deviation is 10, what are the control limits?
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(60, 140)
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(70, 130)
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(80, 120)
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(90, 110)
A
Correct answer
Explanation
The control limits are calculated as the mean plus or minus 4 standard deviations. Therefore, the control limits are 100 +/- 4 * 10 = (60, 140).
What is the formula for calculating MAE?
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MAE = (1/n) * Σ|y_i - y_hat_i|
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MAE = (1/n) * Σ(y_i - y_hat_i)^2
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MAE = (1/n) * Σy_i * y_hat_i
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MAE = (1/n) * Σ(y_i + y_hat_i)
A
Correct answer
Explanation
MAE is calculated by taking the average of the absolute differences between the predicted values (y_hat_i) and the observed values (y_i).
Find the mean of the following numbers: 5, 7, 9, 11, 13
C
Correct answer
Explanation
The mean of a set of numbers is the sum of the numbers divided by the number of numbers. In this case, the mean is (5 + 7 + 9 + 11 + 13) / 5 = 45 / 5 = 9.
What is the formula for calculating mean squared error?
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Mean squared error = (1/n) * Σ(y_i - μ_i)^2
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Mean squared error = (1/n) * Σ(y_i - μ_i)
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Mean squared error = Σ(y_i - μ_i)^2
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Mean squared error = Σ(y_i - μ_i)
A
Correct answer
Explanation
Mean squared error is calculated by taking the average of the squared differences between the predicted values and the actual values.
What is the formula for calculating root mean squared error?
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Root mean squared error = √sqrt((1/n) * Σ(y_i - μ_i)^2)
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Root mean squared error = √sqrt((1/n) * Σ(y_i - μ_i))
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Root mean squared error = √sqrt(Σ(y_i - μ_i)^2)
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Root mean squared error = √sqrt(Σ(y_i - μ_i))
A
Correct answer
Explanation
Root mean squared error is calculated by taking the square root of the mean squared error.