Pr(Z > 1.16) = 0.123
The standard deviation (SD) is a measure of spread so small sd = small spread. So the above is true for any distribution, not just the Normal.
It is not. It depends on what question you want to answer. They are both equally informative, but in different circumstances.the CRFD can be used to determine a summary of proportion of observations that lies above(or below) a particular value in a data set which the RFD cannot
The answer will depend on what the distribution is. Non-statisticians often assum that the variable that they are interested in follows the Standard Normal distribution. This assumption must be justified. If that is the case then the answer is 81.9%
to simply organise your numbers.ajm If you can make a histogram, a dotplot, or even a boxplot; there is no reason to do a steam and leaf plot. It's the worst graph. With a stem and leaf graph, you can see the distribution of data points, and determine whether it's normal distribution or not. As mentioned above, there are better graphs for doing that, though.
z =0 and P(X< x) = 0.5 Explanation: z = (x-xbar)/sd, where xbar is the estimated mean or average of the sample, sd is the standard deviation, and x is the value of the particular outcome. We change x to z so that we can use the normal distribution or t-tables tables, which are based on a zero mean and 1 standard deviation. For example: What is the probability that the mean value of the distribution is 5 or less, given the sample average is 5 and the sd is 2? The z-score would be (5-5)/2 which is equal to 0. The probability, if we assume the normal or t-distribution, is 0.50. (see normal distribution tables) I hope this makes sense to you. The normal distribution is symmetrical. Per the example, a sample average of 5 tells you there is equal chance of the population mean being above and below 5.
It is 0.017864
No, they do not.
The standard deviation (SD) is a measure of spread so small sd = small spread. So the above is true for any distribution, not just the Normal.
0.13
No. By definition of the median, the median has 50 percent of the case below and 50 percent of the cases above. This has nothing to do with the cases being in a normal distribution.
The probability is 0.4448, approx.
2.275 %
It is true. Because the normal distribution is above the horizontal axis for all values, the area under it is a positive quantity no matter the z value.
It is not. It depends on what question you want to answer. They are both equally informative, but in different circumstances.the CRFD can be used to determine a summary of proportion of observations that lies above(or below) a particular value in a data set which the RFD cannot
Yes. The parameters of the t distribution are mean, variance and the degree of freedom. The degree of freedom is equal to n-1, where n is the sample size. As a rule of thumb, above a sample size of 100, the degrees of freedom will be insignificant and can be ignored, by using the normal distribution. Some textbooks state that above 30, the degrees of freedom can be ignored.
It gives a general perspective of the person's height vs fat proportion. It's not accurate specially in athletes or bodybuilders. Less than 23% is considered normal, above 24 overweight and above 30% morbidly obese
It gives a general perspective of the person's height vs fat proportion. It's not accurate specially in athletes or bodybuilders. Less than 23% is considered normal, above 24 overweight and above 30% morbidly obese