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When a population distribution is right skewed is the sampling distribution normal?
No, as you said it is right skewed.
What happens to the graph of the normal curve as the mean increases?
The graph shifts to the right.
What are the characteristics of a normal distribution curve?
Characteristics of a Normal Distribution1) Continuous Random Variable.2) Mound or Bell-shaped curve.3) The normal curve extends indefinitely in both directions, approaching, but never touching, the horizontal axis as it does so.4) Unimodal5) Mean = Median = Mode6) Symmetrical with respect to the meanThat is, 50% of the area (data) under the curve lies to the left ofthe mean and 50% of the area (data) under the curve liesto the right of the mean.7) (a) 68% of the area (data) under the curve is within onestandard deviation of the mean(b) 95% of the area (data) under the curve is within twostandard deviations of the mean(c) 99.7% of the area (data) under the curve is within threestandard deviations of the mean8) The total area under the normal curve is equal to 1.
What proportion of a normal distribution is located between the two z scores -1.25 and 1.25?
Approx 78.88 % Normal distribution tables give the area under the normal curve between the mean where z = 0 and the given number of standard deviations (z value) to its right; negative z values are to the left of the mean. Looking up z = 1.25 gives 0.3944 (using 4 figure tables). → area between -1.25 and 1.25 is 0.3944 + 0.3944 = 0.7888 → the proportion of the normal distribution between z = -1.25 and z = 1.25 is (approx) 78.88 %
What percent of a normal population is within 2 standard deviations of the mean?
In a normal distribution, approximately 95% of the population falls within 2 standard deviations of the mean. This is known as the 95% rule or the empirical rule. The empirical rule states that within one standard deviation of the mean, about 68% of the population falls, and within two standard deviations, about 95% of the population falls.
