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When do you use uniform distribution?
When, over a given range, the probability that a variable in question lies within a particulat interval is equal to the size of that interval as a proportion of the range.
Suppose that a frequency histogram and a cumulative frequency histogram are constructed from the same set of data using the same classes is the frequency for each class is the frequency equal to the?
the frequency is less than OR EQUAL TO the cumulative frequency
The first class in a relative frequency table is 50-59 and the corresponding relative frequency is 0.2What does the 0.2 value indicate?
The sum of the relative frequencies must equal 1 (or 100%), because each individual relative frequency is a fraction of the total frequency. The relative frequency of any category is the proportion or percentage of the data values that fall in that category. Relative frequency = relative in category/ total frequency It means a number in that class appeared 20% of the total appearances of all classes
Does the midpoint of a frequency distribution class equal the sum of the lower and upper limits?
No, the midpoint is the result of adding the upper and lower limits in a class and dividing that by 2. Essentially the mid point is the average of the two limits.
What is the expected value of the standard normal distribution equal to?
The expected value of the standard normal distribution is equal to the total amount of the value. It is usually equal to it when the value works out to be the same.
What is the sum of proportions computed from a frequency distribution have to equal?
The sum of proportions computed from a frequency distribution must equal
What is commulative frequency distribution?
The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x.
What are the benefits of cumulative frequency?
It shows what proportion of the total population are less than (or equal to) each value.
What is sample distribution of the sample proportion?
The sample distribution of the sample proportion refers to the probability distribution of the proportion of successes in a sample drawn from a population. It is typically approximated by a normal distribution when certain conditions are met, specifically when the sample size is large enough (usually np and n(1-p) both greater than 5). The mean of this distribution is equal to the population proportion (p), and the standard deviation is calculated using the formula √[p(1-p)/n]. This distribution is useful for making inferences about the population proportion based on sample data.
What is the mid point of a frequency?
The midpoint of a frequency distribution is the value that divides the distribution into two equal parts. It is calculated by adding the lower and upper limits of a class interval and dividing the sum by 2.
Can a proportion be equal if the cross products are not equal?
No. A cross product is just a way of simplifying a proportion. If the cross product aren't equal, it follows logically that the proportion isn't equal.
What is partial proportion?
partial proportion is equal
What is decile?
Decile means one of the ten groups containing an equal number of the items that make up a frequency distribution.
How can you tell if a proportion is false?
Multiply the cross products, and see if they are equal. If they are equal, the proportion is true. If they are unequal, the proportion is false.
What is the sampling distribution of p hat?
The sampling distribution of (\hat{p}) (the sample proportion) describes the distribution of sample proportions obtained from repeated random samples of a given size from a population. It is approximately normal when the sample size is large enough, typically when both (np) and (n(1-p)) are greater than 5, where (p) is the population proportion and (n) is the sample size. The mean of this distribution is equal to the population proportion (p), and the standard deviation (standard error) is given by (\sqrt{\frac{p(1-p)}{n}}).
When do you use uniform distribution?
When, over a given range, the probability that a variable in question lies within a particulat interval is equal to the size of that interval as a proportion of the range.
What is the meaning of equal proportion?
when you cross multiply you get the same number for each side its an equal proportion
