Summary: Introduction To Statistical Methods And Data Analysis | 9780495109143 | R Lyman Ott, et al

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PLEASE KNOW!!! There are just 76 flashcards and notes available for this material. This summary might not be complete. Please search similar or other summaries.

Read the summary and the most important questions on Introduction to Statistical Methods and Data Analysis | 9780495109143 | R. Lyman Ott, Michael Longnecker.

  • 1 Week 1

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  • 1.1.1 Inference for one or two sample situations

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  • Bij een one-sided test (alpha=0.05) gebruik je in tabel 2, 0.05 of 0.025?

    0.05

  • 1.1.1.1 Two samples

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  • How is it possible the two p-values are not the same?

    df and approximate df are not the same.

  • How is it possible t and t` ( values test statistic) are the same for two independent samples?

    The sample sizes are the same

  • 1.2.2 Smaple size calculations

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  • A type 2 error is denoted by?

    Beta

  • What is the difference between a type 1 and a type 2 error?

    Type 1: Alpha, maximum chance of falsely rejecting H0.

    Type2: Beta, chance of falsely not rejecting H0 while Ha is true.

  • 1.3.1.1 Two indep. samples

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  • If there is a tie on places 10 and 11 what numbers do the two values get?

    10.5

  • 3 Week 3

  • 3.3 Describing data on a single variable: graphical methods

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  • One way to display data graphically, is the pie chart. Obtain clarity of presentation in pie charts by:

    1. Choose a small number (five or six) of categories for the variable because too many make the pie chart difficult to interpret.
    2. Whenever possible, construct the pie chart so that percentages are in either ascending or descending order.
  • A second graphical technique is the bar chart:

    1. Label frequencies one axis and categories of the variable on the other axis.
    2. Construct a rectangle at each categorie of the variable with a height equal to the frequency in the category.
    3. Leave a space between each category to connote distinct, separate categories and to clarify the presentation.
  • Common shapes for relative frequency histograms:

    • Unimodal: a histogram with one major peak
    • Bimodal: a histogram with two major peaks 
    • Uniform: every interval has the same number of observations
    • Symmetric: the right and the left side have essentially the same shape 
    • Skewed to the right: when the right side of the histogram,, containing the larger half of the observations in the data, extends a greater distance than the left side (skewed to the left vice versa).
  • A time series is:

    A pictorial method of presenting changes in a variable over time. Usually, the time points are labeled chronologically across the horizontal axis and the numerical values of the variable of interest are labeled along the vertical axis.
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