Practice: the correlation coefficient and the regression line

Statistics, grade 11 (4 units) Lesson 19 of 20Practice

Practice: the correlation coefficient and the regression line

1

Grade 12 pupils wrote a project, and its mark counted in the final mark.
The teacher drew a scatter diagram: $\displaystyle x$ – the project mark, $\displaystyle y$ – the final mark.

a

Can you conclude from the diagram that every pupil whose project mark is higher than another pupil’s also got a higher final mark? Explain.

b

One of these numbers is the correlation coefficient: $\displaystyle 1.6$ , $\displaystyle -0.8$ , $\displaystyle 0.999$ , $\displaystyle 0$ , $\displaystyle 0.675$ . Which? Explain.

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

c

$\displaystyle {\bar{x}}={71}$ , $\displaystyle {S_x}={23}$ ; $\displaystyle {\bar{y}}={75}$ , $\displaystyle {S_y}={14}$ .
Find the equation of the regression line predicting the final mark from the project mark. Round the slope to two decimal places.

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

d

What is the predicted final mark of a pupil whose project mark is 90?

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

2

In a kindergarten the children were asked how many sweets they eat a day ( $\displaystyle x$ ) and how many pretzels ( $\displaystyle y$ ).

$\displaystyle x$	1	2	3	4	5	6
$\displaystyle y$	6	5	4	3	2	1

a

Work out $\displaystyle S_x$ , to two decimal places.

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

b

Work out the correlation coefficient.

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

c

How can you tell what the correlation coefficient will be before working it out?

3

$\displaystyle x$	2	4	6	8	10
$\displaystyle y$	3	4	8	7	13

Work out the correlation coefficient, to two decimal places.

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

4

In the tablet shop from the lesson on computing the correlation coefficient: the screen size $\displaystyle x$ – $\displaystyle {\bar{x}}={10}$ , $\displaystyle {S_x}={1}$ ; the decision time $\displaystyle y$ – $\displaystyle {\bar{y}}={10}$ , $\displaystyle {S_y}={4}$ ; $\displaystyle {r}={0.5}$ .

a

Find the equation of the regression line predicting the decision time from the screen size, and write it on the board.

b

The shop ordered a new model with a 12-inch screen. What is the predicted decision time for this model?

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

5

A researcher measured pupils’ heights in centimetres and their weights in kilograms, and got $\displaystyle {r}={0.82}$ .
Another researcher measured the same pupils in inches and pounds.
What correlation coefficient did the second researcher get? Explain.

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – check and a new line · * – times · ^ – power, ↓ – end of the power

/ – fraction bar · Tab or the arrows – between numerator and denominator, then a note above or below · Enter – a new line · * – times · ^ – power, ↓ – end of the power

6

Across Israeli towns, the correlation coefficient between the number of cafés in a town and the number of doctors in it is $\displaystyle {r}={0.9}$ .
A mayor suggested opening cafés so that more doctors come to the town. What do you think? Explain.

Formulas: statistics, grade 11 (4 units)

The mean and the standard deviation

The mean – $\displaystyle f_1, \dots, f_n$ the frequencies, $\displaystyle N$ the number of data
$\displaystyle \bar{x}=\frac{x_1f_1+x_2f_2+\dots+x_nf_n}{N}$
The standard deviation
$\displaystyle S=\sqrt{\frac{(x_1-\bar{x})^{2}f_1+(x_2-\bar{x})^{2}f_2+\dots+(x_n-\bar{x})^{2}f_n}{N}}$

The standard score

The standard score of the value $\displaystyle x$
$\displaystyle z=\frac{x-\bar{x}}{S}$
The value whose standard score is $\displaystyle z$
$\displaystyle x=\bar{x}+z\cdot S$

The normal distribution

The standard score in a normal distribution – $\displaystyle \mu$ the mean, $\displaystyle \sigma$ the standard deviation
$\displaystyle z=\frac{x-\mu}{\sigma}$
Within one standard deviation of the mean
$\displaystyle P(\mu-\sigma<X<\mu+\sigma)\approx68\%$
Within two standard deviations of the mean
$\displaystyle P(\mu-2\sigma<X<\mu+2\sigma)\approx95\%$
Above a standard score
$\displaystyle P(Z>z)=1-P(Z<z)$
The curve’s symmetry
$\displaystyle P(Z>z)=P(Z<-z)$
Between two standard scores
$\displaystyle P(z_1<Z<z_2)=P(Z<z_2)-P(Z<z_1)$

The cumulative standard normal table

In the table: the row – $\displaystyle z$ to its first decimal place; the column – the second. In a negative row the column goes further from 0: row $\displaystyle -1.2$ , column 3 holds $\displaystyle \Phi(-1.23)$ .
$\displaystyle \Phi(z)=P(Z<z)$

`z`	0	1	2	3	4	5	6	7	8	9
-3.0	0.0013	0.0013	0.0013	0.0012	0.0012	0.0011	0.0011	0.0011	0.0010	0.0010
-2.9	0.0019	0.0018	0.0018	0.0017	0.0016	0.0016	0.0015	0.0015	0.0014	0.0014
-2.8	0.0026	0.0025	0.0024	0.0023	0.0023	0.0022	0.0021	0.0021	0.0020	0.0019
-2.7	0.0035	0.0034	0.0033	0.0032	0.0031	0.0030	0.0029	0.0028	0.0027	0.0026
-2.6	0.0047	0.0045	0.0044	0.0043	0.0041	0.0040	0.0039	0.0038	0.0037	0.0036
-2.5	0.0062	0.0060	0.0059	0.0057	0.0055	0.0054	0.0052	0.0051	0.0049	0.0048
-2.4	0.0082	0.0080	0.0078	0.0075	0.0073	0.0071	0.0069	0.0068	0.0066	0.0064
-2.3	0.0107	0.0104	0.0102	0.0099	0.0096	0.0094	0.0091	0.0089	0.0087	0.0084
-2.2	0.0139	0.0136	0.0132	0.0129	0.0125	0.0122	0.0119	0.0116	0.0113	0.0110
-2.1	0.0179	0.0174	0.0170	0.0166	0.0162	0.0158	0.0154	0.0150	0.0146	0.0143
-2.0	0.0228	0.0222	0.0217	0.0212	0.0207	0.0202	0.0197	0.0192	0.0188	0.0183
-1.9	0.0287	0.0281	0.0274	0.0268	0.0262	0.0256	0.0250	0.0244	0.0239	0.0233
-1.8	0.0359	0.0351	0.0344	0.0336	0.0329	0.0322	0.0314	0.0307	0.0301	0.0294
-1.7	0.0446	0.0436	0.0427	0.0418	0.0409	0.0401	0.0392	0.0384	0.0375	0.0367
-1.6	0.0548	0.0537	0.0526	0.0516	0.0505	0.0495	0.0485	0.0475	0.0465	0.0455
-1.5	0.0668	0.0655	0.0643	0.0630	0.0618	0.0606	0.0594	0.0582	0.0571	0.0559
-1.4	0.0808	0.0793	0.0778	0.0764	0.0749	0.0735	0.0721	0.0708	0.0694	0.0681
-1.3	0.0968	0.0951	0.0934	0.0918	0.0901	0.0885	0.0869	0.0853	0.0838	0.0823
-1.2	0.1151	0.1131	0.1112	0.1093	0.1075	0.1056	0.1038	0.1020	0.1003	0.0985
-1.1	0.1357	0.1335	0.1314	0.1292	0.1271	0.1251	0.1230	0.1210	0.1190	0.1170
-1.0	0.1587	0.1562	0.1539	0.1515	0.1492	0.1469	0.1446	0.1423	0.1401	0.1379
-0.9	0.1841	0.1814	0.1788	0.1762	0.1736	0.1711	0.1685	0.1660	0.1635	0.1611
-0.8	0.2119	0.2090	0.2061	0.2033	0.2005	0.1977	0.1949	0.1922	0.1894	0.1867
-0.7	0.2420	0.2389	0.2358	0.2327	0.2296	0.2266	0.2236	0.2206	0.2177	0.2148
-0.6	0.2743	0.2709	0.2676	0.2643	0.2611	0.2578	0.2546	0.2514	0.2483	0.2451
-0.5	0.3085	0.3050	0.3015	0.2981	0.2946	0.2912	0.2877	0.2843	0.2810	0.2776
-0.4	0.3446	0.3409	0.3372	0.3336	0.3300	0.3264	0.3228	0.3192	0.3156	0.3121
-0.3	0.3821	0.3783	0.3745	0.3707	0.3669	0.3632	0.3594	0.3557	0.3520	0.3483
-0.2	0.4207	0.4168	0.4129	0.4090	0.4052	0.4013	0.3974	0.3936	0.3897	0.3859
-0.1	0.4602	0.4562	0.4522	0.4483	0.4443	0.4404	0.4364	0.4325	0.4286	0.4247
-0.0	0.5000	0.4960	0.4920	0.4880	0.4840	0.4801	0.4761	0.4721	0.4681	0.4641
0.0	0.5000	0.5040	0.5080	0.5120	0.5160	0.5199	0.5239	0.5279	0.5319	0.5359
0.1	0.5398	0.5438	0.5478	0.5517	0.5557	0.5596	0.5636	0.5675	0.5714	0.5753
0.2	0.5793	0.5832	0.5871	0.5910	0.5948	0.5987	0.6026	0.6064	0.6103	0.6141
0.3	0.6179	0.6217	0.6255	0.6293	0.6331	0.6368	0.6406	0.6443	0.6480	0.6517
0.4	0.6554	0.6591	0.6628	0.6664	0.6700	0.6736	0.6772	0.6808	0.6844	0.6879
0.5	0.6915	0.6950	0.6985	0.7019	0.7054	0.7088	0.7123	0.7157	0.7190	0.7224
0.6	0.7257	0.7291	0.7324	0.7357	0.7389	0.7422	0.7454	0.7486	0.7517	0.7549
0.7	0.7580	0.7611	0.7642	0.7673	0.7704	0.7734	0.7764	0.7794	0.7823	0.7852
0.8	0.7881	0.7910	0.7939	0.7967	0.7995	0.8023	0.8051	0.8078	0.8106	0.8133
0.9	0.8159	0.8186	0.8212	0.8238	0.8264	0.8289	0.8315	0.8340	0.8365	0.8389
1.0	0.8413	0.8438	0.8461	0.8485	0.8508	0.8531	0.8554	0.8577	0.8599	0.8621
1.1	0.8643	0.8665	0.8686	0.8708	0.8729	0.8749	0.8770	0.8790	0.8810	0.8830
1.2	0.8849	0.8869	0.8888	0.8907	0.8925	0.8944	0.8962	0.8980	0.8997	0.9015
1.3	0.9032	0.9049	0.9066	0.9082	0.9099	0.9115	0.9131	0.9147	0.9162	0.9177
1.4	0.9192	0.9207	0.9222	0.9236	0.9251	0.9265	0.9279	0.9292	0.9306	0.9319
1.5	0.9332	0.9345	0.9357	0.9370	0.9382	0.9394	0.9406	0.9418	0.9429	0.9441
1.6	0.9452	0.9463	0.9474	0.9484	0.9495	0.9505	0.9515	0.9525	0.9535	0.9545
1.7	0.9554	0.9564	0.9573	0.9582	0.9591	0.9599	0.9608	0.9616	0.9625	0.9633
1.8	0.9641	0.9649	0.9656	0.9664	0.9671	0.9678	0.9686	0.9693	0.9699	0.9706
1.9	0.9713	0.9719	0.9726	0.9732	0.9738	0.9744	0.9750	0.9756	0.9761	0.9767
2.0	0.9772	0.9778	0.9783	0.9788	0.9793	0.9798	0.9803	0.9808	0.9812	0.9817
2.1	0.9821	0.9826	0.9830	0.9834	0.9838	0.9842	0.9846	0.9850	0.9854	0.9857
2.2	0.9861	0.9864	0.9868	0.9871	0.9875	0.9878	0.9881	0.9884	0.9887	0.9890
2.3	0.9893	0.9896	0.9898	0.9901	0.9904	0.9906	0.9909	0.9911	0.9913	0.9916
2.4	0.9918	0.9920	0.9922	0.9925	0.9927	0.9929	0.9931	0.9932	0.9934	0.9936
2.5	0.9938	0.9940	0.9941	0.9943	0.9945	0.9946	0.9948	0.9949	0.9951	0.9952
2.6	0.9953	0.9955	0.9956	0.9957	0.9959	0.9960	0.9961	0.9962	0.9963	0.9964
2.7	0.9965	0.9966	0.9967	0.9968	0.9969	0.9970	0.9971	0.9972	0.9973	0.9974
2.8	0.9974	0.9975	0.9976	0.9977	0.9977	0.9978	0.9979	0.9979	0.9980	0.9981
2.9	0.9981	0.9982	0.9982	0.9983	0.9984	0.9984	0.9985	0.9985	0.9986	0.9986
3.0	0.9987	0.9987	0.9987	0.9988	0.9988	0.9989	0.9989	0.9989	0.9990	0.9990

The correlation coefficient

From raw data
$\displaystyle r=\frac{1}{N\cdot S_x\cdot S_y}\left[(x_1-\bar{x})(y_1-\bar{y})+\dots+(x_N-\bar{x})(y_N-\bar{y})\right]$
From standardised data – $\displaystyle z_x$ , $\displaystyle z_y$ the standard scores
$\displaystyle r=\frac{1}{N}\left[(z_x)_1(z_y)_1+\dots+(z_x)_N(z_y)_N\right]$
Always between $\displaystyle -1$ and $\displaystyle 1$
$\displaystyle -1\le r\le1$

The regression line

The slope of the regression line
$\displaystyle m=r\cdot\frac{S_y}{S_x}$
The regression line predicting $\displaystyle y$ from $\displaystyle x$ – through the point of the means
$\displaystyle y-\bar{y}=m(x-\bar{x})$