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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.
4.764.724.744.554.914.744.784.714.804.784.784.754.794.824.914.834.684.744.704.804.704.764.704.834.934.744.844.824.764.774.724.784.834.754.744.684.844.714.714.764.664.784.734.744.924.774.804.794.864.644.784.704.754.784.764.834.664.774.834.784.694.814.684.784.884.724.854.854.814.744.804.824.844.704.854.704.814.724.794.63
- What is the
mean ,median , andmode ? (you may want to use your calculator or the average and medianfunctions in Excel!) - What could be some reasons for variation in the weights of the Kisses®? Note: Take time answering this one. There are lots of things to consider here and I'll be looking for a well thought out answer with several given reasons contributing to the variation. Of course, the wrappers and tags could vary but what about the drops of chocolate themselves? Why aren't they all the same?
- Would you say that there are any two Kisses that have exactly the same weight? (I mean exactly the same weight!) Explain why or why not.
- How many Kisses® were there in the bag?
- Based on Hershey's® claim for 368 total net grams of chocolate in the bag, approximately how many Kisses® too many or too few are there? Assume that the Kisses® were weighed with the wrapper, each wrapper weighs 0.12 grams, and the net grams listed on the bag are for the chocolate only. Give some possible explanations for this difference.
- Make a histogram of the data using 8-to-10 classes. You can either use Excel or hand-draw it. If you hand-draw it, make sure your picture or scan of the histogram is easy to read!
- Describe the distribution of Kisses®. Make sure to include descriptions of the shape, center, spread, and outliers, if there are any.
- In general, each Kiss® is approximately how many grams? Explain what measure you used and why.
- Standard Deviation & the
Empirical Rule : Variation is a big factor in the analysis of most any data set and it will be very important to have a way of measuring it. Standard Deviation is one such measure. Find the Standard Deviation of the data. You can use the stdev or stdev.s functions in Excel. A bell-shaped distribution with a single peak is called anormal distribution . There is a rule for normal distributions that can help you have some feeling for what the standard deviation is telling you. It's called the Empirical Rule and is stated below:
For any data set having a Normal distribution, the following are true:
- Approximately 68% of the data values will be within one standard deviation of the mean.
- Approximately 95% of the data values will be within two standard deviation of the mean.
- Approximately 99.7% of the data values will be within three standard deviation of the mean.
Use the mean (to the nearest thousandth), the standard deviation (to the nearest thousandth), and the Empirical Rule to find answers to the following:
a) Find the percentage of all the Kisses in the bag that fell within 1 standard deviation of the mean? ... within 2?… within 3? (Show how you calculated these percentages!)
b) How close is the Empirical Rule in predicting the percentages that you calculated above?
c) If your calculated percentages did not line up with the percentages claimed by the Empirical Rule, speculate on some possible reasons for this. - How might standard deviation and the shape of the distribution indicate how consistent Hershey® is in the manufacturing of their Kisses®?
- What did you learn from doing this lab? What did you enjoy the most?
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