A Manager of a car company wants to estimate the relationship between age of cars and annual
maintenance cost. The following data from six cars of same model are obtained as:
| Age of Car (in years) | Annual Maintenance Cost (In hundred rupees) |
| 1 | 10 |
| 2 | 15 |
| 3 | 18 |
| 4 | 20 |
| 5 | 25 |
| 6 | 35 |
(a) Construct a scatter diagram for the data given above.
(b) Fit a best linear regression line, by considering annual maintenance cost as the dependent variable and the age of the car as the independent variable.
(c) Use this regression line to predict the annual maintenance cost for the car of age 8 years.
We are asked to solve this step by step manually. Given data: | Age of Car (x) | Maintenance Cost (y) | | -------------- | -------------------- | | 1 | 10 | | 2 | 15 | | 3 | 18 | | 4 | 20 | | 5 | 25 | | 6 | 35 | --- Step (a): Scatter diagram A scatter diagram is simply a plot of points $(x, y)$: * Point 1: (1, 10) * Point 2: (2, ____ _________ ______ ________ _________ __________ _____ ______ ___ ____.
_____ _________ ____ __________ ______ _________.
__________ ____ _________ _________ __________ __________ ___ ________.
______ ____ ______ _______ ________.
_______ ____ _______ ____ ___ __________ ___ ___ ___ _______ _______.
_______ ________ _____ ___ _____ _______ ____ _________ _________.
__________ ________ _________ _______ _________ ____ _____ ______ ________ ___.
_______ _____ _____ ________ ________ __________ ________ ____ ______.
_________ ________ _______ __________ ____.
________ ___ ______ _____ _______.
_________ _____ _____ _______ ______ _______.
__________ _____ _________ _________ _______ _________ _________ __________.
___ ________ __________ _______ _____ ______ _______.
_______ ______ ______ ______ __________ ______ ________ __________ ____ __________.
____ ________ ________ _______ _______.
_________ _________ _________ _______ _________ ________ _____ ______ ____ ______ ______.
__________ ____ _____ _____ __________ ___ ___ ____.
____ ________ _________ ____ _______ ___.
_________ _______ _______ ________ _____ _________ _______ ________ _______ _____ ______.
______ _________ _________ __________ _________ ___ ______ ______ __________ _____ ______.
________ ______ __________ __________ ________ __________ ___ ________ _____ __________.
___ _____ ___ __________ _____ ______ ________.
_________ _________ ________ _______ ______ ______ _____ __________ __________ _________ _____ ____.
____ _____ ___ _________ ___ ___.
______ ______ _____ ___ ___ _________ _________ ___ __________ _____.
_________ _______ ______ ___ ________ _______ ________ ________ _____.
__________ ______ _________ _____ ________ _______ __________ _____ ____ ___ ___.
_____ _________ _____ ___ ____.
________ ______ ______ _________ ________.
________ ______ ________ ______ ________ _____ _________ _______ ________ __________ _________ __________.
_____ _____ ___ ________ _____ __________ ________ __________ ____.
____ _______ _____ _____ ____ ___ ______.
_______ __________ ________ ______ __________ ______ ______ ________ ____ ____ _________ _________.
___ ___ ______ _____ ________.
_____ _____ _______ ________ ______ _________ _________ ___ _________ __________ ___ _____.
__________ ____ ______ _________ __________ _________ __________ ___ ____ ____ _________ ____.
______ ______ __________ ______ ___.
_________ __________ ______ ___ ____ ___ _________ _________.
_______ __________ _________ ________ ____ ____ _____ ____ ______ ________.
___ ____.
Get Full Answer on WhatsApp
A computer chip manufacturer claims that at most 2% of the chips it produces are defective.
To check the claim of the manufacturer, a researcher selects a sample of 250 of these chips. If there are eight defective chips among these 250, test the null hypothesis that more than 2% of the chips are defective at 5% level of significance. Does this disprove the manufacturer's claim? (Given that Zooς = 1.645)
Z-test and t-test
Using the Regression line y =90 + 50x, fill up the values in the table below
| SAMPLE No. (i) | 12 | 21 | 15 | 1 | 24 |
| 0.96 | 1.28 | 1.65 | 1.84 | 2.35 | |
| 138 | 160 | 178 | 190 | 210 | |
| 138 | - | - | - | - | |
| 0 | - | - | - | - |
What do you understand by the term forecasting? With the help of a suitable example discuss the relation between forecasting and future planning. Briefly discuss both forecasting model.
A problem of statistics is given to three students A, B and C whose chances of solving it are 0.3, 0.5 and 0.6 respectively. What is the probability that the problem will be solved?
(i) 3 defectives in a sample of 100
(ii) no defectives in a sample of 50
In a partially destroyed laboratory, the legible record of analysis of correlation of data, is as follows: 10
Variance of x = 9, Regression equations:
8x-10y+66=0
4x-18y-214-0
What were (a) the means of x and y, (b) the coefficient of correlation between x and y and (c) the standard deviation of y?
Linear and circular systematic sampling