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- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/05%3A_Discrete_Probability_Distributions/5.08%3A_Chapter_5_FormulasDiscrete Distribution Variance: σ 2 = ∑(x i 2 ∙P(x i )) – μ 2 Geometric Distribution: P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … Binomial Distribution: P(X = x) = n C x ·p x ·q (n-x ) , x = 0, 1, 2, … ...Discrete Distribution Variance: σ 2 = ∑(x i 2 ∙P(x i )) – μ 2 Geometric Distribution: P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … Binomial Distribution: P(X = x) = n C x ·p x ·q (n-x ) , x = 0, 1, 2, … , n Hypergeometric Distribution: P(X = x) = \(\frac{a C_{x} \cdot {}_b C_{n-x}}{ _{N} C_{n}}\) Unit Change for Poisson Distribution: New μ = old μ(\(\frac{\text { new units }}{\text { old units }}\)) Poisson Distribution: P(X = x) = \(\frac{e^{-\mu} \mu^{x}}{x !}\)
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/02%3A_Organizing_Data/2.03%3A_Graphical_DisplaysThe shape of the histogram will be the same for the relative frequency distribution and the frequency distribution; the height, though, is the proportion instead of frequency. You can have your output...The shape of the histogram will be the same for the relative frequency distribution and the frequency distribution; the height, though, is the proportion instead of frequency. You can have your output default to a new worksheet, or select the circle to the left of Output Range, click into the box to the right of Output Range and then select one blank cell on your spreadsheet where you want the top left-hand corner of your table and graph to start.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/04%3A_Probability/4.01%3A_IntroductionMore important questions that probability can help with are your chances that the car you are buying will need more maintenance, your chances of passing a class, your chances of winning the lottery, o...More important questions that probability can help with are your chances that the car you are buying will need more maintenance, your chances of passing a class, your chances of winning the lottery, or your chances of catching a deadly virus. The bottom sideway V assumes that a blue marble was drawn on the first draw, and then the second marble drawn can be either red or blue.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/02%3A_Organizing_Data/2.02%3A_Tabular_DisplaysWhen creating frequency distributions, it is important to note that the number of classes that are used and the value of the first class boundary will change the shape of, and hence the impression giv...When creating frequency distributions, it is important to note that the number of classes that are used and the value of the first class boundary will change the shape of, and hence the impression given by, the distribution.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/05%3A_Discrete_Probability_Distributions/5.02%3A_Discrete_Probability_DistributionsNote this is a valid probability distribution because the probability of each x, P(x), is between 0 and 1, and the probability of the sum of all x values from 0 to 3 is ∑ P (x) = \(\frac{1}{8}+\frac{3...Note this is a valid probability distribution because the probability of each x, P(x), is between 0 and 1, and the probability of the sum of all x values from 0 to 3 is ∑ P (x) = \(\frac{1}{8}+\frac{3}{8}+\frac{3}{8}+\frac{1}{8}=1\). This is a probability distribution since you have the x value and the probabilities that go with it, all of the probabilities are between zero and one, and the sum of all of the probabilities is one.
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/12%3A_Nonparametric_TestsThis chapter provides alternative methods to some of the previously covered, parametric tests (z-, t-, and F-tests) when the assumptions necessary for these parametric tests are not met. Includes the ...This chapter provides alternative methods to some of the previously covered, parametric tests (z-, t-, and F-tests) when the assumptions necessary for these parametric tests are not met. Includes the sign test, Wilcoxon signed-rank test, and the Mann-Whitney U test.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/07%3A_Confidence_Intervals_for_One_PopulationDeveloping confidence intervals based on a sample for a single population.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/12%3A_Correlation_and_Regression/12.02%3A_Simple_Linear_Regression/12.2.04%3A_PredictionUse the regression equation to predict the grade for a student who has studied for 18 hours for their exam using the previous data. The \(x\)-variable is the hours studied so let \(x = 18\) hours. \(\...Use the regression equation to predict the grade for a student who has studied for 18 hours for their exam using the previous data. The \(x\)-variable is the hours studied so let \(x = 18\) hours. \(\hat{y}\) is the symbol for the predicted \(y\). TI-89: Enter the \(x\)-values in list1 and the \(y\)-values in list2, select [F7] Intervals, then select option 7:LinRegTInt… Use the Var-Link button to enter in list1 and list2 for the X List and Y List.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/zz%3A_Back_Matter/10%3A_Index
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/00%3A_Front_Matter/01%3A_TitlePageMostly Harmless Statistics (Webb)
- https://stats.libretexts.org/Workbench/Introduction_to_Statistical_Methods_(Yuba_College)/07%3A_Continuous_Probability_Distributions/7.03%3A_Normal_DistributionThe normalcdf on the calculator needs the lower and upper value of the shaded area followed by the mean and standard deviation. (The TI-89 uses -∞ for the lower boundary instead of -1E99.) If you want...The normalcdf on the calculator needs the lower and upper value of the shaded area followed by the mean and standard deviation. (The TI-89 uses -∞ for the lower boundary instead of -1E99.) If you want to find the area above a point, or between two points, then find the area below a point by using the complement rule and keep in mind that the total area under the curve is 1 and the total area below the mean is 0.5.
