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- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Book%3A_Visual_Statistics_Use_R_(Shipunov)/00%3A_Front_Matter/01%3A_TitlePageMinot State University Visual Statistics Use R! Alexey Shipunov
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Book%3A_Visual_Statistics_Use_R_(Shipunov)/02%3A_How_to_process_the_data/2.08%3A_R_graphicsIn the base, default installation, several dozens of plot types are already present, more are from recommended lattice package, and much more are in the external packages from CRAN where more than a h...In the base, default installation, several dozens of plot types are already present, more are from recommended lattice package, and much more are in the external packages from CRAN where more than a half of them (several thousands!) is able to produce at least one unique type of plot. If the next command is of the same type, R will erase the content of the device and start the new plot.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Book%3A_Visual_Statistics_Use_R_(Shipunov)/03%3A_Types_of_Data/3.07%3A_Changing_data-_basics_of_transformationsIn complicated studies involving many data types: measurements and ranks, percentages and counts, parametric, nonparametric and nominal, it is useful to unify them. It may normalize data with negative...In complicated studies involving many data types: measurements and ranks, percentages and counts, parametric, nonparametric and nominal, it is useful to unify them. It may normalize data with negative skew (left-tailed) data, bring relationships between variables closer to linear and equalize variances. At the end of data types explanation, we recommend to review a small chart which could be helpful for the determination of data type (Figure \(\PageIndex{1}\)).
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/03%3A_Probability/3.02%3A_Three_Types_of_ProbabilityThe sample space is S = {1, 2, 3, 4, 5, 6}. The event A is that you want is to get a 4, and the event space is A = {4}. Thus, in theory the probability of rolling a 4 would be P(A) = 1/6 = 0.1667.
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/04%3A_Discrete_Probability_Distributions/4.03%3A_Geometric_DistributionsThe geometric distribution is P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … where x is the number of trials up to the first success that you are trying to find the probability for, p is the probability of...The geometric distribution is P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … where x is the number of trials up to the first success that you are trying to find the probability for, p is the probability of a success for one trial and q = 1 – p is the probability of a failure for one trial.
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/05%3A_Continuous_Probability_Distributions/5.02%3A_Uniform_DistributionThe probability is found by taking the area between two points within the rectangle formed from the x-axis, between the endpoints a and b, the length, and f(x) = 1/(b-a), the height. When working with...The probability is found by taking the area between two points within the rectangle formed from the x-axis, between the endpoints a and b, the length, and f(x) = 1/(b-a), the height. When working with continuous distributions it is helpful to draw a picture of the distribution, then shade in the area of the probability that you are trying to find. a) First plug in the endpoints a = 0 and b = 15 into the PDF to get the height of the rectangle.
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/08%3A_Hypothesis_Tests_and_Confidence_Intervals_for_Two_Populations/8.04%3A_Two_Variance_or_Standard_Deviation_F-TestIf your test statistic is less than 1, then find the area to the left of the test statistic, if F is above 1 then find the area to the right of the test statistic. Then type in the s 1 , n 1 , s 2 , n...If your test statistic is less than 1, then find the area to the left of the test statistic, if F is above 1 then find the area to the right of the test statistic. Then type in the s 1 , n 1 , s 2 , n 2 , arrow over to the \(\neq\), <, > sign that is the same in the problem’s alternative hypothesis statement, then press the [ENTER] key, arrow down to [Calculate] and press the [ENTER] key.
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/06%3A_Confidence_Intervals_for_One_Population/6.04%3A_Z-Interval_for_a_MeanIf the sample size is “large” (n ≥ 30) the Central Limit Theorem guarantees that the sampling distribution of the mean will be normally distributed no matter how the population distribution is distrib...If the sample size is “large” (n ≥ 30) the Central Limit Theorem guarantees that the sampling distribution of the mean will be normally distributed no matter how the population distribution is distributed. It is easier to deal with the positive z-score so use the z to the right of the mean which would have 1 – \(\alpha\)/2 = 0.975 area.
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/05%3A_Continuous_Probability_Distributions/5.07%3A_Continuous_Probability_ExercisesCompute the area under the curve of the standard normal distribution that is within 1.328 standard deviations from either side of the mean. The amount of time to complete a physical activity in a PE c...Compute the area under the curve of the standard normal distribution that is within 1.328 standard deviations from either side of the mean. The amount of time to complete a physical activity in a PE class is normally distributed with a mean of 33.2 seconds and a standard deviation of 5.8 seconds. Match the following 3 graphs with the distribution of the population, the distribution of the sample, and the sampling distribution.
- 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/Workbench/Statistics_for_Behavioral_Science_Majors/12%3A_Nonparametric_Tests/12.04%3A_Wilcoxon_Signed-Rank_TestApplying the Wilcoxon Signed-Rank Sum test as the non-parametric alternative to the dependent t-test; includes multiple worked examples.
