consists of organizing and summarizing data and describes data through numerical summaries, tables, and graphs.
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inferential statistics
uses methods that take a result from a sample, extend it to the population, and measure the reliability of the result
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population
the entire group of people/objects to be studied
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sample
a subset of the population being studied
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simple random sampling
\ a sample completed in a way that every sample of size n has an equal chance of being selected
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discrete variable
\ one that takes on a finite or countably infinite values: no decimal/fractions, Ex. number of siblings, number of dual credits taken, etc.
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continuous variable
\ takes on an infinite values - decimals/fractions Ex. time, temperature, height, weight, etc.
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Distribution Shapes
bell-shaped, uniform, right-skewed, left-skewed
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Measures of Center
\ mean, median, mode,
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measures of variation
\ range, standard deviation, variance, inter-quartile range
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standard deviation
\ descriptive measure that describes the overall spread of a data set from the mean
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resistant measures
\ descriptive measures that are not impacted by extremes, Ex. median, mode, inter-quartile range
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left skewed
\ the mean would be less than the median (extreme values impact the mean)
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bell shaped
\ the mean would be equal to the median
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right skewed
\ the mean would be greater than the median (extreme values impact the mean)
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Approximately 68% of the data falls within
\ 1 standard deviation of the mean
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Approximately 95% of the data falls within
2 standard deviations of the mean
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Approximately 99.7% of the data falls within
\ 3 standard deviations of the mean
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parameter
\ a descriptive measure for a population
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statistic
\ a descriptive measure for a sample
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z-score
\ tells you the number of standard deviations an observation is from the mean of the data set.
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mutually exclusive events
\ two or more events that do not have any outcomes in common or they cannot happen at the same time.
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independent events
\ Events A and B are independent if P(A) = P(A/B) or P(B) = P(B/A)
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permutation
\ An ordered arrangement in which r objects are chosen from n distinct (different) objects so that r < n and repetition is not allowed: Use nPr
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combination
\ A collection, without regard to order, in which r objects are chosen from n distinct objects with r < n and without repetition: Use nCr
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empirical rule for binomial experiments - unusual events
\ np(1-p) > 10, Unusual if it falls outside of the 2 standard deviation range
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linear correlation coefficient - r
measure of the strength and direction of the linear relation between two quantitative variables - the closer the value r is to 1 the stronger the positive/negative linear correlation
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**coefficient of determination** - r^2
\ the percent of variation in the y variable that can be explained by the variation in the x variable
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least squares regression line
\ the line that minimizes the sum of the squared errors (or residuals).
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interpretation of slope
\ As the x variable changes by 1 unit the y variable changes by the value of the slope in your equation.
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\n **interpretation of y-intercept**
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the value of y when x = 0. To interpret you must have x values close to zero and it needs to make sense for the problem
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normally distributed variable
\ bell shaped - centered at the mean within + and - 3 standard deviations
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standard normal distribution
\ the z distribution - centered at 0, bell shaped, the mean is 0 and standard deviation 1
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sampling error
\ the error resulting from using a sample to estimate a population characteristic.
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relation between sample size and sampling error
\ As the sample size increases, the precision increases (the width of the C. I. decreases)
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Central Limit Theorem
\ if X is not normally distributed then the Central Limit Theorem states x-bar will be normally distributed if the sample size n 30.
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point estimate
\ the value of a statistic used to estimate a parameter - x bar, p hat
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relation between confidence and precision
\ As the confidence level increases the precision decreases (the width of the C.I. interval is increases)
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margin of error
\ the distance from the point estimate to the end of the confidence interval
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interpretation of a confidence interval
\ We are _______% confident that the population mean/proportion (describe the variable) is between __________ and __________.