Standard normal distribution:
The Standard normal distribution is a normal distribution with a mean of “0” and a standard deviation of “1”. Normal distribution can be transformed to standard normal distribution by formula:
Z= (X - µ)/ б
Where X is a score from the original normal distribution, µ is the mean of the original normal distribution, and б is the standard deviation of original normal distribution. The standard normal distribution is sometimes call the Z distribution.
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Bayes' Theorem
Statistics can prove anything’
‘Figures cannot lie’
Comment on the above two statements, indicating reasons for the existence of such divergent views regarding the nature and functions of statistics
From the following data compute quartile deviation and the coefficient of skewness:
Standard normal distribution:
A restaurant is experiencing discontentment among its customers. It analyses that there are three factors responsible viz. food quality, service quality and interior décor. By conducting an analysis, it assesses the probabilities of discontentment with the three factors as 0.40, 0.35 and 0.25 respectively. By conducting a survey among the customers, it also evaluated the probabilities of a customer going away discontented on account of these factors as 0.6, 0.8 and 0.5, respectively. With this information, the restaurant wants to know that, if a customer is discontented, what are the probabilities that it is so due to food, service or interior décor?
Bayes' Theorem
Exponential Smoothing Method