The marks obtained by 10 students in a Statistics test are 24, 47, 18, 32, 19, 15, 21, 35, 50 and 41.
The question asks us to calculate the Mean Deviation for the largest five observations from a given set of marks obtained by 10 students in a Statistics test. The marks are: 24, 47, 18, 32, 19, 15, 21, 35, 50, and 41.
First, we need to identify the largest five observations from the list. To do this, we should arrange the marks in ascending order:
15, 18, 19, 21, 24, 32, 35, 41, 47, 50
From the sorted list, the largest five observations are:
32, 35, 41, 47, 50
Next, we calculate the mean (average) of these five observations. Let's denote these observations as \(x_1, x_2, x_3, x_4, x_5\).
The mean (\(\bar{x}\)) is calculated using the formula:
\(\bar{x} = \frac{\sum_{i=1}^{5} x_i}{5}\)Substituting the values:
\(\bar{x} = \frac{32 + 35 + 41 + 47 + 50}{5}\) \(\bar{x} = \frac{205}{5}\) \(\bar{x} = 41\)So, the mean of the largest five observations is 41.
The Mean Deviation (MD) is the average of the absolute differences between each observation and the mean.
The formula for Mean Deviation is:
\(MD = \frac{\sum_{i=1}^{5} |x_i - \bar{x}|}{5}\)Now, we calculate the absolute difference of each of the largest five observations from their mean (which is 41):
Finally, we calculate the Mean Deviation by averaging these absolute differences:
\(MD = \frac{9 + 6 + 0 + 6 + 9}{5}\) \(MD = \frac{30}{5}\) \(MD = 6\)The Mean Deviation of the largest five observations (32, 35, 41, 47, 50) from the given dataset is 6.
What is the median height of the class?
What is the total number of students whose height is less than or equal to 165 cm?
The height which occurs most frequently in the class is
Methods of presentation of data are:
Consider 35 i.i.d. observations X1, X2, ...., X15 and Y1, Y2, ..., Y20. Let R be the Wilcoxon's rank sum statistic based on the ranks of the X' s in the combined sample. Then the expected value of R is
Let I, J > 5. Consider two-way ANOVA, where the observations satisfy the linear model
yij = α + βi + γj + εij, 1 ≤ i ≤ I, 1 ≤ j ≤ J
E(εij) = 0, Var(εij) = σ2, \(\sum_{i=1}^{!} β_i=\sum_{j=1}^j γ_j=0 .\)
In this set - up
Let X1,X2,...,Xn be a random sample from exponential distribution with mean θ. Which of the following is NOT a sufficient statistic for θ?
A newly developed algorithm for random number generation needs to be tested. The first step is to check whether the sequence of numbers generated can be considered a random sample from the uniform distribution on the interval (0, 1). Which of the following is an appropriate nonparametric test?