1. The document discusses the relationship between two variables and defines correlation coefficients ranging from 0 to 1 to indicate the strength of their relationship. 2. It then provides an example of a fruit shake store owner studying the correlation between temperature and sales over 12 summer days. Data is presented on the temperature, sales, and calculations for correlation analysis. 3. The results of the correlation analysis show a significant association between temperature and total sales, indicating higher temperatures are correlated with increased fruit shake sales.

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3. 

4. 

5. 

11. Coefficient Relationship
0.00 No correlation, no relationship
Very low correlation, almost
negligible relationship
Slight correlation, definite but small
relationship
Moderate correlation, substantial
relationship
High correlation, marked
relationship
Very high correlation, very
dependable relationship
Perfect correlation, perfect
relationship

12. 

13.  Subjects are randomly selected.
 Both populations are normally distributed

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15. 

16.  When the null hypothesis has been rejected for a specific significance
level, there are possible relationships between X and Y variables:
1. There is a direct cause-and-effect relationship between the two
variables.
2. There is a reverse cause-and-effect relationship between the
two variables.
3. The relationship between the two variables may be caused by the
third variable.
4. There maybe a complexity of interrelationship among many
variables.
5. The relationship between the two variables may be coincidental.

17. The owner of a chain of fruit shake stores would
like to study the correlation between
atmospheric temperature and sales during the
summer season. A random sample of 12 days is
selected with the results given as follows:

18. DAY TOTAL SALES
1 147
2 76 143
3 78 147
4 84 168
5 90 206
6 83 155
7 93 192
8 94 211
9 97 209
10 85 187
11 88 200
12 82 150

19. 140
150
160
170
180
190
200
210
220
75 80 85 90 95 100
TOTALSALES
TEMPERATURE

20. 

21. DAY X Y X2 Y2 XY
1 79 147 6,241 21,609 11,613
2 76 143 5,776 20,449 10,868
3 78 147 6,084 21,609 11,466
4 84 168 7,056 28,224 14,112
5 90 206 8,100 42,436 18,540
6 83 155 6,889 24,025 12,865
7 93 192 8,649 36,864 17,856
8 94 211 8,836 44,521 19,834
9 97 209 9,409 43,681 20,273
10 85 187 7,225 34,969 15,895
11 88 200 7,744 40,000 17,600
12 82 150 6,724 22,500 12,300
TOTAL

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24. 

25.  Since the null hypothesis has been rejected, we can
conclude that there is evidence that shows significant
association between the atmospheric temperature and
the total sales of fruit shake.