Statistics for IT– Worldwideasy – 08

Statistics for IT– Worldwideasy – 08

Statistics for IT– Worldwideasy – 08 to you today Demonstrate knowledge of Continuous Random Variables.

If a random variable is possible, it is continuous Assume an infinite number of values Correspond to the points of a linear gap.

Continuous Probability Distribution

Suppose we measure the height of the students in this class. If we
“Discrete” to the nearest feet, to the discrete The probability histogram is shown on the left. If tall now Measured to the nearest inch, the probability is a histogram Shown in the middle. We get more pots and smoother the appearance. Suppose we proceed in this way to measure height More and more subtly, probabilistic histograms as its counterpart Enter a smooth curve shown on the right.

Probability Distribution for a Continuous
Random Variable

The probability distribution describes how probability exists Distributed on all possible values. probability distribution for Continuous random variables are determined by x arithmetic The function denoted by f (x) is called the dens function. The graph of a function is a smooth curve.

The Normal Distribution

The Statistics generating formula Average probability distribution:

Two parameters, mean and standard deviation, Determine the average distribution completely. The shape and location of the average curve very Difference between mean and standard deviation.

Using Table 3 – Statistics

The probability of four digits in a particular row and column Table 3 gives the area under the standard average The curve between 0 and the positive value is z. This is enough Since the standard average curve is symmetric

  • Read on to find an area between …. 0 and the positive z value Straight from the table.
  • Use the properties of the standard average curve Probability laws for finding other fields.

Working Backwards Statistics

Most of the time we know the area and want to find the z value It gives the area. Example: Find the value of positive z with an area Between 47750 0 and z.

The Normal Approximation to the

We can calculate binary probabilities

  • Binary formula Cumulative binary tables When n is large, and when p is not close to zero One, areas with mean np under the normal curve And variability npq can be used approximately Binary probabilities.

Thank for all!

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