Final
Quiz yourself by thinking what should be in
each of the black spaces below before clicking
on it to display the answer.
Help!
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| Centeral Limit Theorem | As the sample size n increases without limit, the shape of the distribution of the sample means taken with replacement from a population with mean and standard deviation or will approach a normal distribution.
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| Type I | Occurs if you reject the null hypothesis when it is true.
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| Type II | Occurs if you do not reject the null hypothesis when it is false.
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| Critical Region | The range of calues of the test value that indicates that there is a significant difference and that the null hypothesis should be rejected.
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| Two tailed test | The type of hypothesis in which the alternative claims that the mean is not equal to a particular value rather the claim is greater or less that that value.
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| One tailed test | Either a right tailed test or left tailed test depending on the direction of the inequaliity of the alternavie hypothesis.
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| Degree of freedom for the t test | The number of values that are free to vary after a sample statistic has been computed, and they tell the researched which specific curve to use when a distribution consists of a family of curves.
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| Level of significance | The maximum probability of committing a type I eror.
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| P-value | The probability of getting a sample statistic or a more extreme sample statistic in the direction of the alternative hypothesis when the null hypothesis is true.
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| Permutation | An arrangement of n objects in a specific order.
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| Combination | A selection of distinct objects without regard to order/
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| 2 major branches of statistics | Descriptive statistics Inferential Statistics
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| 4 reasons why samples are used in statistics | It saves time Less costly Provides room for better accuracy and effectiveness Product conservativeness It allows the use of more qualified hands/professionals and better equipments
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| Standard deviation measure | The sum of dispersion or distance of individual value away from the mean.
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| Outlier | An extremely high or extremely low data value when compared with the rest of the data values.
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| Chebyshev's theorem | The proportion of values from a data set that will fall within k standard deviations of the mean will be at least 1-1/k squared, where k is a number greater than 1 (k is not necessarily an integer).
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| Characteristics of the binomial distribution | Must be a fixed number of trials. Each trial can have only 2 outcomes or can be reduced to 2 considered either success or failure. Outcome of each trial must be independent of one another. The probability of a success must remain same for each trial
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Created by:
LDBradley
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