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Published on: 23/06/2021
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Questions + Answers key
Take MCQ Economics Test1.
Distinguish between correlation and regression.
2.
Explain the steps involved computing the correlation Coefficient.
3.
Distinguish between Qualitative and Quantitative data.
4.
Compare and contrast primary and secondary data.
5.
Calculate the standard deviation for the following data by assumed mean method: 43, 48, 65, 57, 31, 60, 37, 48, 78, 59
1.
| S.No | Correlation | Regression |
| 1 | Correlation is the relationship between two or more variables, which vary with the other in the same or the opposite direction |
Regression means going back and it is a mathematical measure showing the average relationship between two variables |
| 2 | Both the variables X and Y are random variables |
Both the variables may be random variables |
| 3 | It finds out the degree of relationship between two variables and not the cause and effect relationship. |
It indicates the cause and effect relationship between the variables and establishes functional relationship. |
| 4 | It is used for testing and verifying the relation between two variables and gives limited information |
Besides verification it is used for the prediction of one value, in relation to the other given value. |
| 5 | The coefficient of correlation is a relative measure. The range of relationship lies between –1 and +1 |
Regression coefficient is an absolute figure. If we know the value of the independent variable, we can find the value of the dependent variable |
| 6 | There may be spurious correlation between two variables. |
In regression there is no such spurious regression |
| 7 | It has limited application, because it is confined only to linear relationship between the variables |
It has wider application, as it studies linear and nonlinear relationship between the variables |
| 8 | It is not very useful for further mathematical treatment. |
It is widely used for further mathematical treatment |
2.
Procedure for Computing the Correlation Coefficient: (For Direct and Deviation from actual mean method).
Step- 1 Calculate the mean of two series ‘X’’Y’
Step- 2 Calculate the deviations ‘X’ and Y in two series from their respective mean.
Step- 3 Square each deviations of ‘X’ and ‘Y’ then obtain the sum of the Squared deviation,
Step- 4 Multiply each deviation under X with each deviation under Y and obtain the product of ‘xy’. Then obtain the sum of the product of X, Y. Then obtain the sum of the product of x,y is Σxy.
Step- 5 Substitute the value in the formula.
3.
1. Find out the actual mean of given data (x̅)
2. Find out the deviation of each value from the mean (x = X - x̅ )
3. Square the deviations and take the total of squared deviations Σx2
4. Divided the total Σx2 by the number of observation \(\left( { \frac { \sum { x } }{ n } }^{ 2 } \right) \)
5. The square root of \(\left( { \frac { \sum { x } }{ n } }^{ 2 } \right) \) is standard deviation.
| BASIS FOR COMPARISON |
QUALITATIVE DATA | QUANTITATIVE DATA |
| Meaning | Qualitative data is the data in which the classification of objects is based on attributes and properties. |
Quantitative data are those that can be quantified in definite units of measurement |
| Examples | Eg. Gender, Community, honesty | Age, income, number of firms etc |
| Approach | Subjective | Objective |
| Collection of data | Unstructured | Structured |
| Sample | Small number of nonrepresentative samples |
Large number of representative samples |
| Outcome | Develops initial understanding. | Recommends final course of action |
4.
| BASIS FOR COMPARISON |
PRIMARY DATA | SECONDARY DATA |
| Meaning | Those data which do not ready exist in any form, and thus have to be collected for the first time from the primary source(s). | They already exist in zome form: published or npublished in an identifiable secondary source. |
| Nature | Real time data - first-time collected | Past data - available from published source(s) |
| Process | Very involved | Quick and easy |
| Source | Surveys, observations, experiments, questionnaire, personal interview, etc. |
Government publications, websites, books, journal articles, internal records etc. Eg. Data from CSO, NSSO, RBI |
| Cost-effectiveness | Expensive | Economical |
| Collection time | Long | Short |
| Form | Crude form | Refined form |
| Accuracy and Reliability | More | Relatively less |
5.
| S.No | (X) | D=X-A(A=57) | (X-\(\bar { X } \))2 |
| 1 | 43 | -14 | 196 |
| 2 | 48 | -9 | 87 |
| 3 | 65 | 8 | 64 |
| 4 | 57 | 0 | 0 |
| 5 | 31 | -26 | 679 |
| 6 | 60 | 3 | 9 |
| 7 | 37 | -20 | 400 |
| 8 | 48 | -9 | 81 |
| 9 | 78 | 21 | 441 |
| 10 | 59 | 2 | 4 |
| N-9 | \(\sum { d } =44\) | \(\sum { d }^2 =1952\) |
\(\sigma =\sqrt { \frac { { \sum { d } }^{ 2 } }{ n } -\frac { { (\sum { d } ) }^{ 2 } }{ (n) } } =\sqrt { \frac { 1952 }{ 10 } -\frac { { (-44) }^{ 2 } }{ (10) } } \)
\(=\sqrt { 195.2-19.36 } =\sqrt { 175.84 } =13.26\)
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Biology

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Computer Applications

Computer Science

Business Maths and Statistics

Commerce

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Chemistry

Physics

Computer Technology

History

Accountancy

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