Binomial Distribution

Experimental probability is the fraction of times an event actually occurs and theoretical probability is the fraction of times we would expect an event to occur. I did not know these terms until after I read the article. The article shown me that there are so many ways to approach probability. It gave me an idea of using the line chart as an assessment of understanding probability. The number cube game gave me an idea of teaching probability by playing Yahtzee

The cumulative probability of outcomes from 4 to 20 is .6%. The outcome parameters were 4 to 20 because, we were specifically asked to look at the probability of Four-D rejecting >=4 or more shipments in 20 days.

(a) Then mean of the sample and the value of Z with an area of 10% in right tail.

10 . Eighteen percent of men prefer brand A of a certain product. Suppose 5 men are

Find P(12 < x < 23) when mu = 19 and sigma = 6. Write your steps in probability notation.

σB = 0.3 × (0.14)2 + 0.4 × (0.04)2 + 0.3 × (0.08)2 − (0.05)2 = 0.00594.

8. Question : Which of the following is a provision of the central limit theorem?

5. Find the sample variance s2 for the following sample data. Round your answer to the nearest hundredth.

3. List the probability value for each possibility in the binomial experiment that was calculated in MINITAB with the probability of a success being ½. (Complete sentence not necessary)

A statistical example for random variable is coin toss that refers to the discrete random variable as it will get the outcomes in discrete number.

Dice Throw, while it can be calculated using math to project the probability of getting a particular number.

Experimental probability of an event is the ratio of the number of times the event occurs to the total number of trials.

For every statistical experiment, an alternative hypothesis and a null hypothesis is constructed. If "the variance between groups exceeds what is expected in terms of the variance" the null has been disproven and the independent variable is shown to have had a measurable influence upon the experimental population (Analysis of variance. 2012, Stat Primer). In statistical experimentation, the hypothesis (which the experimenter actually thinks or hopes will occur) is never technically proven; rather the null hypothesis is refuted. The actual hypothesis of the experimenter is 'guilty until proven innocent' (What is a null hypothesis, 2012, Null Hypothesis).

= NPV (normal) * 0.7 + NPV (best) * 0.2 + NPV (worst) * 0.1

b. What is the probability of failing on the first 2 trials and passing on the