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Evaluate: `int (2"e"^"x" - 3)/(4"e"^"x" + 1)` dx
Concept: undefined >> undefined
Evaluate: `int "e"^"x" (1 + "x")/(2 + "x")^2` dx
Concept: undefined >> undefined
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Evaluate: `int "x" * "e"^"2x"` dx
Concept: undefined >> undefined
Evaluate: `int log ("x"^2 + "x")` dx
Concept: undefined >> undefined
Evaluate: `int "e"^sqrt"x"` dx
Concept: undefined >> undefined
Evaluate: `int sqrt("x"^2 + 2"x" + 5)` dx
Concept: undefined >> undefined
Evaluate: `int sqrt(x^2 - 8x + 7)` dx
Concept: undefined >> undefined
Choose the correct alternative:
There are ______ types of regression equations
Concept: undefined >> undefined
The HRD manager of a company wants to find a measure which he can use to fix the monthly income of persons applying for the job in the production department. As an experimental project, he collected data of 7 persons from that department referring to years of service and their monthly incomes.
| Years of service (X) | 11 | 7 | 9 | 5 | 8 | 6 | 10 |
| Monthly Income (₹ 1000's)(Y) | 10 | 8 | 9 | 5 | 9 | 7 | 11 |
- Find the regression equation of income on years of service.
- What initial start would you recommend for a person applying for the job after having served in a similar capacity in another company for 13 years?
Concept: undefined >> undefined
Calculate the regression equations of X on Y and Y on X from the following data:
| X | 10 | 12 | 13 | 17 | 18 |
| Y | 5 | 6 | 7 | 9 | 13 |
Concept: undefined >> undefined
From the following data estimate y when x = 125.
| X | 120 | 115 | 120 | 125 | 126 | 123 |
| Y | 13 | 15 | 14 | 13 | 12 | 14 |
Concept: undefined >> undefined
The following table gives the aptitude test scores and productivity indices of 10 workers selected at random.
| Aptitude score (X) | 60 | 62 | 65 | 70 | 72 | 48 | 53 | 73 | 65 | 82 |
| Productivity Index (Y) | 68 | 60 | 62 | 80 | 85 | 40 | 52 | 62 | 60 | 81 |
Obtain the two regression equations and estimate the productivity index of a worker whose test score is 95.
Concept: undefined >> undefined
The following table gives the aptitude test scores and productivity indices of 10 workers selected at random.
| Aptitude score (X) | 60 | 62 | 65 | 70 | 72 | 48 | 53 | 73 | 65 | 82 |
| Productivity Index (Y) | 68 | 60 | 62 | 80 | 85 | 40 | 52 | 62 | 60 | 81 |
Obtain the two regression equations and estimate the test score when the productivity index is 75.
Concept: undefined >> undefined
Compute the appropriate regression equation for the following data:
| X [Independent Variable] |
2 | 4 | 5 | 6 | 8 | 11 |
| Y [dependent Variable] | 18 | 12 | 10 | 8 | 7 | 5 |
Concept: undefined >> undefined
The following are the marks obtained by the students in Economics (X) and Mathematics (Y)
| X | 59 | 60 | 61 | 62 | 63 |
| Y | 78 | 82 | 82 | 79 | 81 |
Find the regression equation of Y on X.
Concept: undefined >> undefined
From the following data obtain the equation of two regression lines:
| X | 6 | 2 | 10 | 4 | 8 |
| Y | 9 | 11 | 5 | 8 | 7 |
Concept: undefined >> undefined
For the following data, find the regression line of Y on X
| X | 1 | 2 | 3 |
| Y | 2 | 1 | 6 |
Hence find the most likely value of y when x = 4.
Concept: undefined >> undefined
From the following data, find the regression equation of Y on X and estimate Y when X = 10.
| X | 1 | 2 | 3 | 4 | 5 | 6 |
| Y | 2 | 4 | 7 | 6 | 5 | 6 |
Concept: undefined >> undefined
The following sample gives the number of hours of study (X) per day for an examination and marks (Y) obtained by 12 students.
| X | 3 | 3 | 3 | 4 | 4 | 5 | 5 | 5 | 6 | 6 | 7 | 8 |
| Y | 45 | 60 | 55 | 60 | 75 | 70 | 80 | 75 | 90 | 80 | 75 | 85 |
Obtain the line of regression of marks on hours of study.
Concept: undefined >> undefined
The following data gives the production of bleaching powder (in '000 tons) for the years 1962 to 1972.
| Year | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 |
| Production | 0 | 0 | 1 | 1 | 4 | 2 | 4 | 9 | 7 | 10 | 8 |
Fit a trend line by graphical method to the above data.
Concept: undefined >> undefined
