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.
- Make a Stem-Leaf Plot 2. Box-Whisker Plot 3. Label all of the parts of the Box-Whisker plot. 4. Identify outliers if there are any.
- 22 15 18 20 12 16 15 25 11 14
- 35 26 2 22 37 42 40 29 24
- 24 27 17 12 28 13 20 27 15 21 50
Section 3:
- Label all of the parts of the Normal Distribution Curve Below.
Section 4: Standard Deviation
Follow the steps below to find the standard deviation for the following data.
12 18 24 7 15 12 9 10 13 21 Mean=_______________ Numbers Data - Mean Squared
Total
Mean of the differences Squared______________
Standard Deviation=_____________
“Since you have asked multiple questions, we will solve the first question for you. If you want any specific question to be solved then please specify the question number or post only that question.”
a)
The following procedure is used to construct a stem and leaf plot for the given data,
- Enter the data into Minitab worksheet.
- Select Graph, Stem and Leaf.
- Under Variables, select the variable containing the temperature values.
- Enter 10 for Increment.
- Click OK.
Output:
Thus, the stem and leaf plot is constructed for the given data.
b)
The following procedure is used to construct a box and whisker plot,
- Enter the data into Minitab worksheet.
- Select Graph, Boxplot.
- Under Variables, select the variable containing the data values.
- Click OK.
Output:
The lower and upper limits values for detecting the outliers are,
Thus, the lower and upper limits values for detecting the outliers are -3.375 and 45.625.
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