Question

George has found a relationship between the height of a person and his bowling score. The table below shows the data collected by George.
Height cm
152 160 164 170 180 162 154 158 168
Bowling Score
51 55 57 60 65 55 52 54 59
Prt A: What would most likely be the bowling score of a person who has a height of 156 cm?
Prt B: Predict a possible correlation coefficient for the data in the table and explain why you think your prediction is a good value for the data.

Answer 1

You first need to find the regression line

Answer 2

how?

Answer 3

what kind of calculator do you have?

Answer 4

i can use an online calculator

Answer 5

ok you can use something like this

http://www.alcula.com/calculators/statistics/linear-regression/

Answer 6

okay, one moment please

Answer 7

height is x?

Answer 8

@jim_thompson5910

Answer 9

correct

Answer 10

@jim_thompson5910 regression line

Answer 11

it was 52.8 round?

Answer 12

I'm getting the same results

Answer 13

52.8 ?

Answer 14

oh for part A

Answer 15

I'm getting 52.8757396449703

that rounds to 52.9 if you're rounding to 1 decimal place

Answer 16

if you're rounding to the nearest whole number, you get 53

Answer 17

should i put 53?

Answer 18

yeah why not (to be consistent with the other data values)

Answer 19

okay for part b: i get 0.99708278548604 as the correlation coefficent

Answer 20

me too

Answer 21

should i put 1

Answer 22

that is very very close to 1, and no, don't round

Answer 23

if it were perfectly 1, then all of the points would lie on a straight line

Answer 24

but the fact that it's very very close to 1 means that nearly all of the points lie on a straight line (it's very close)

Answer 25

okay for my reasoning can i put it is closer to 1 so it indicates a strong positive relationship

Answer 26

positive linear, yeah

Answer 27

Part C: George says that if the bowling ball is rolled with a greater force, the bowling score will be higher. Is this an example of correlation or causation? Justify your answer.

Answer 28

thats part c

Answer 29

what do you think about it?

Answer 30

causatoin?

Answer 31

well unless you can prove it by isolating all of the variables, it's hard to show causation

there could be other factors involved

Answer 32

a lot of people mix up correlation and causation

Answer 33

so it's correlation? it's hard to distinguish them

Answer 34

it's correlation until you can show a stronger connection

Answer 35

there may be other factors at play (like skill level or something)

Answer 36

so how can i justify?

Answer 37

have a look at this page

http://rationalwiki.org/wiki/Correlation_does_not_imply_causation

Answer 38

in it, it says

"Simple example

Two events can consistently correlate with each other but not have any causal relationship. An example is the relationship between reading ability and shoe size across the whole population of the United States. If someone performed such a survey, they would find that the larger shoe sizes correlate with better reading ability, but this does not mean large feet cause good reading skills. Instead it's caused by the fact that young children have small feet and have not yet (or only recently) been taught to read. In this case, the two variables are more accurately correlated with a third: age. "