hat a population of thousands of p
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
Assume that a population of thousands of people whose responses were used to develop the anxiety test had scores that were
- Below 20 =
- Above 30
- Between 10 and 50 =
- Below 10 =
- Below 50 =
- Above 50 =
- Either below 10 or above 50 =
What is SEm2? It is the sample estimate of the standard error of the mean. What does the value of SEm tell you about the typical magnitude of sampling error? It tells where a researcher has one sample of data of size N and the researcher can compute a sample mean, M, and a sample standard deviation, s, but the researcher does not know the values of the population parameter.
- As s increases, how does the size of SEm change (assuming that N stays the same)?
- As N increases, how does the size of SEm change (assuming that s stays the same)
Let’s suppose that a researcher wants to set up a 95% CI for IQ scores using the following information:
The sample mean M= 130
The sample standard deviation s = 15.
The
The df = N – 1 = 119
- What are the upper and lower limits of the CI and the width of the 95% CI if all the other values remain the same (M = 130, s =15) but you change the value of N to 16
- What are the upper and lower limits and the width of this Ci if you change the confidence level to 80% (and continue to use M = 130, s = 15, and N = 49)? For an 80% CI, lower limit = and upper limit = width (upper limit – lower limit) =
- What are the upper and lower limits and width of the CI if you change the confidence level to 99% (continue to use M= 130, s =15, and N =49)? For a 99% CI, lower limit = and upper limit = width (upper limit – lower limit) =
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