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  2. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    Z tables use at least three different conventions: . Cumulative from mean gives a probability that a statistic is between 0 (mean) and Z.Example: Prob(0 ≤ Z ≤ 0.69) = 0.2549.

  3. File:Normal Distribution PDF.svg - Wikipedia

    en.wikipedia.org/wiki/File:Normal_Distribution...

    English: A selection of Normal Distribution Probability Density Functions (PDFs). Both the mean, μ , and variance, σ² , are varied. The key is given on the graph.

  4. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The simplest case of a normal distribution is known as the standard normal distribution or unit normal distribution. This is a special case when μ = 0 {\textstyle \mu =0} and σ 2 = 1 {\textstyle \sigma ^{2}=1} , and it is described by this probability density function (or density): φ ( z ) = e − z 2 2 2 π . {\displaystyle \varphi (z ...

  5. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    Let's say we have a sample with size 11, sample mean 10, and sample variance 2. For 90% confidence with 10 degrees of freedom, the one-sided t value from the table is 1.372 . Then with confidence interval calculated from

  6. List of common display resolutions - Wikipedia

    en.wikipedia.org/wiki/List_of_common_display...

    The difference is that whilst D1 has a 4:3 aspect ratio 960H has a 16:9 widescreen aspect ratio. The extra pixels are used to form the increased area to the sides of the D1 image. The pixel density of 960H is identical to standard D1 resolution so it does not give any improvement in image quality, merely a wider aspect ratio.

  7. Standard score - Wikipedia

    en.wikipedia.org/wiki/Standard_score

    Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.

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  9. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    Difference between Z-test and t-test: Z-test is used when sample size is large (n>50), or the population variance is known. t-test is used when sample size is small (n<50) and population variance is unknown. There is no universal constant at which the sample size is generally considered large enough to justify use of the plug-in test.