Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
Measures of Dispersion
Box 3: Food vs. Oil
Below are the figures for foodgrain procurement and crude oil production during 20x1-x2
Month
Foodgrain Procurement ('000 tonnes)
Crude Oil Production (lakh tonnes)
20x1
April
3,506
23.5
May
3,558
23.2
June
285
22.3
July
65
23.0
August
25
22.9
September
782
22.1
October
2,473
22.6
November
1,920
21.8
December
2,403
20x2
January
2,300
February
1,603
20.1
March
837
22.4
Total
19,757
269.1
The variability of the crude oil figures is much less than those of the foodgrain figures. This can be seen from the fact that all the crude oil production figures lie within 11% of the mean value of 22.4 lakh tonnes (i.e. between 19.9 lakh tonnes and 24.9 lakh tonnes). On the other hand only one foodgrain figure, i.e. February 20x2 procurement lies within 11% of the mean procurement value of 1646.4 thousand tonnes (between 1465.3 lakh tonnes and 1827.5 lakh tonnes). Hence the mean is a more representative value for the crude oil data as compared with the foodgrain data.
In the case of foodgrain procurement, the monthly figures vary from a low of 25 thousand tonnes in August 20x1 to a high of 3558 thousand tonnes in May 20x1. This is due to the seasonal nature of agriculture.
In the case of crude oil production, the monthly figures vary from a low of 20.1 lakh tonnes in February 20x2 to a high of 23.5 lakh tonnes in April 20x1.
The above vignette reveals that while a mean may give the central tendency of data, it does not reveal anything about the variability or dispersion of the data. For this another measure is needed.
The variability or dispersion of data is given by measures of dispersion.
When there is no dispersion, all the data points have identical values and the values of all the measures of central tendency converge.
Testing of Hypothesis One objective of sampling theory is Hypothesis Testing. Hypothesis testing begins by making an assumption about the population parameter. Then we gather
Linear Regression Generally, in two mutually related statistical series, the regression analysis based on graphic method. Under graphic method the values of X and Y variable
A. Compute descriptive statistics for each stock and the S&P 500. Comment on your results. Which stocks are most volatile?
Correlation The correlation is commonly used and a useful statistic used to describe the degree of the relationships between two or more variables. Pearson's correlation refle
1. Calculate the mean and mode of: Central size 15 25 35 45 55 65 75 85 Frequencies 5 9 13 21 20 15 8 3 The following data shows the monthly expenditure of 80 students of
Sampling A Population is a collection of all the data points being studied. For example, if we are studying the annual incomes of all the people in India, then the population
practical application of standard error
I need help
Statistical Errors Statistical data are obtained either by measurement or by observation. Hence to think of perfect accuracy is only a delusion or a myth, It is no
12 shoppings in nairobi 38/week
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +1-415-670-9521
Phone: +1-415-670-9521
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd