Nine students took the SAT. Their scores are listed below. Later on, they took a preparation course and retook the SAT. Their new scores are listed below. Test the claim that the test preparation had no effect on their scores. Use α = 0.05. Assume that the distribution is normally distributed. STUDENT 1 2 3 4 5 6 7 8 9 Score Before 720 860 850 880 860 710 850 1200 950 Score After 740 860 840 920 890 720 840 1240 970
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
Nine students took the SAT. Their scores are listed below. Later on, they took a preparation course and retook the SAT. Their new scores are listed below. Test the claim that the test preparation had no effect on their scores. Use α = 0.05. Assume that the
|
STUDENT |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
|
Score Before |
720 |
860 |
850 |
880 |
860 |
710 |
850 |
1200 |
950 |
|
Score After |
740 |
860 |
840 |
920 |
890 |
720 |
840 |
1240 |
970 |
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