background image

 

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HP 30S Statistics – Linear Regression

 

 
Answer: 

10.89 grams. 

=

)

.

('

x

5

10

=

)

.

(

5

10

 
Example 4:  The previous examples are based on the regression of the final concentration (y) on the amount of 

chemical added (x). Would the last result obtained be equal to 

if we were studying the regression 

of x on y

)

.

('

y

5

10

 
Solution: 

The most likely answer is no. y is the dependent variable and x is the independent variable. Their roles 

 

cannot be interchanged. If we interchange x and y, we change our experiment, the results of which may 
well be meaningless. Let’s see what happens, by swapping the given data, and then we’ll find 

.  

Press 

a

and reenter the data in the following order: 

)

.

('

y

5

10

 

 

3?2???5?6?5?3???8?6?8.5?9?

 

 

 To 

find 

 press: 

)

.

('

y

5

10

 
 

 

b@@@@@@@@

 (to select  ) 

y10.5y

 

'

y

 
Answer: 

According to the new regression, the predicted value is 9.88 grams. The regression line is now 

 (where x is still the amount of chemical added and y is the concentration), which 

y

.

.

x

98

0

38

0

+

=

 is 

not the same as before (

y

.

.

x

18

1

44

1

+

=

 
Example 5:  By polling fifty people, a survey taker obtained the following data: 
 
 

and 

 

3333

=

i

x

9

459

.

y

i

=

231933

2

=

i

x

57

4308

2

.

y

i

=

75

30549

.

y

x

i

i

=

 
 

Judging by the correlation coefficient , is there a linear relation between x and y?  

 
Solution: 

 r can be calculated using the formula given on page 2: 

 





=

50

9

459

57

4308

50

3333

231933

50

9

459

3333

75

30549

2

2

.

.

.

.

r

 

 

 

Let’s enter it into the entry line by pressing: 

 

 

r30549.75-333*459.9/50s 
/pr231933-3333q/50sr43 
08.57-459.9q/50

and finally  

y

.

 

 
Answer: 

r = –0.12, so we can assume there’s no linear relation at all. 

 
 
 

hp calculators 

- 4 - 

HP 30S Statistics – Linear Regression - Version 1.0 

Summary of Contents for HP 30S

Page 1: ...hp calculators HP 30S Statistics Linear Regression Linear Regression Practice Solving Linear Regression Problems ...

Page 2: ...greement between the x and y variables and is given by n y y n x x n y x y x r i i i i i i i i 2 2 2 2 When r is positive the correlation is positive which means that high values of one variable correspond to high values of the other Conversely if r is negative then the correlation is negative low values of one variable correspond to high values of the other An important property of r is that 1 1 ...

Page 3: ...ressed to two decimal digits a 1 22 and b 0 85 therefore the regression line is The correlation coefficient is 0 91 which means that the correlation is positive and that it is quite a good fit since r is close to 1 However exactly how far away from this value the correlation can be and the equation still be considered a good predictor is certainly a matter of debate x y 85 0 22 1 Example 2 If the ...

Page 4: ... 5 9 To find press y 5 10 b to select y10 5y y Answer According to the new regression the predicted value is 9 88 grams The regression line is now where x is still the amount of chemical added and y is the concentration which y x 98 0 38 0 is not the same as before y x 18 1 44 1 Example 5 By polling fifty people a survey taker obtained the following data and 3333 i x 9 459 yi 231933 2 i x 57 4308 ...

Page 5: ...s that point 610 15 6 is anomalous and is consequently removed from the data set To do so press Figure 1 a seven times and e NB not o The new correlation coefficient is displayed as above i e by pressing b and then the left arrow key six times Answer r 0 9997 so there s strong evidence that the relation is linear The regression line is x y 01 0 03 8 Example 7 Find the power curve that best fits th...

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