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12 Cards in this Set
- Front
- Back
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PMCC Product moment correlation coefficient |
It is always between -1 and +1 |
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when pmcc is 1
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This means it has a perfectly positive correleation |
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when pmcc is -1
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This means it has a perfectly negative correlation
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Two conditions of the pmcc is that
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1 data should come from a RANDOM sample 2 data should form an ellipse on scatter diagram so an elliptical shape should form |
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PHRASING THE ANSWER
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r is closer to 1 than the critical value, so the result is significant, reject H0 in favor of H1 This means there is evidence to suggest that at the 5 % significant level, x and y are positivelty correlated (must be no correlation, positive correlation or negative correlation) |
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what to write on the hypothesis |
ho; p=0 h1;p>< or not equal to 0
or phrase it in words, eg no correlation between x and y, then state what p represents |
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what is p in hypothesis test
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P is the population correlation coefficient
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the expected value table
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always use four significant figures
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Critical value of two tail test !!!
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You mustn't move down 5% 2.5% 1% 0.5% 10% 5% 2% 1% n 1 0.1 0.2 0.3 0.4 2 0.5 0.6 0.7 0.8 the critical value for n=1, 5% level 2 tail test should be 0.2 not 0.6 DONT MOVE DOWN STAY IN THE SAME COLOME |
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Significance level's definition
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The probability of rejecting H0 when it is in fact truth
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State an advantage and a disadvantage of using a 1% significance level rather than 5 % significance level
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Advantage of 1% level – less likely to reject H0 when it is true. Disadvantage of 1% level – less likely to accept H1 when H0 is false. |
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The student decides to take another random sample of 10 plums. Using the same hypotheses as in part (ii), the correlation coefficient for this second sample is significant at the 5% level. The student decides to ignore the first result and concludes that there is correlation between the length and circumference of plums in the crop. (iv) Comment on the student’s decision to ignore the first result. Suggest a better way in which the student could proceed. [3] |
The student’s approach is not valid. If a statistical procedure is repeated with a new sample, we should not simply ignore one of the two outcomes. The student could combine the two sets of data into a single set of twenty measurements. |
