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2.2.3. Discrete vs. Continuous Probability Distributions

            A continuous probability distribution is composed of continuous variables, as opposed to a discrete probability
            distribution, which is composed of discrete variables. Other differences between the two types of distributions
            also exist.
            Consider the following graph of men’s heights probability distribution:

                                                    50

                                       Probability


                                                    30


                                                                   50%    50%
                                                    10


                                                             60        70       80
                                                                 Height (Inches)
            The probability, that a particular random variable will equal a certain value, is zero. For example, let’s say you had
            a continuous probability distribution for men’s heights. What is the probability that a man will have a height of
            exactly 70 inches? The chart shows that the average man has a height of 70 inches (50% of the area of the curve is
            to the left of 70, and 50% is to the right). But it’s impossible to figure out the probability of any one man measuring
            exactly 70 inches. Why not? Imagine measuring a man who is 70 inches tall. It’s unlikely that he’s exactly 70 inches.
            He’s probably 70.1 inches, or perhaps 69.97 inches. And it doesn’t stop there. He could be 70.1045 inches, or
            69.9795589 inches. The fact is, it’s impossible to exactly measure any variable that’s on a continuous scale, and
            so it’s impossible to figure out the probability of one exact measurement occurring in a continuous probability
            distribution.


            2.3. STATISTICAL PROBLEM-SOLVING PROCESS

            To gather and analyse data in order to respond to statistical inquiry questions is the goal of the statistical problem
            solving process. Each of the four components of this investigative method involves examining and addressing
            variability:







                                             Step

                                              by
                                             Step                              Target





                                                                        Interpret the
                                                                        Data
                                                               Analyse the
                                                               Data
                                                     Collect/consider
                                                     the data
                                             Plan: Formulate
                                             Standard Investigative
                                             Questions

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