• Descriptive
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    • Cross Correlation Function
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  1. Appendices
  2. F  Critical values of Student’s \(t\) distribution with \(\nu\) degrees of freedom
  • Preface
  • Getting Started
    • 1  Introduction
    • 2  Why Do We Need Innovative Technology?
    • 3  Basic Definitions
    • 4  The Big Picture: Why We Analyze Data
  • Introduction to Probability
    • 5  Definitions of Probability
    • 6  Jeffreys’ axiom system
    • 7  Bayes’ Theorem
    • 8  Sensitivity and Specificity
    • 9  Naive Bayes Classifier
    • 10  Law of Large Numbers

    • 11  Problems
  • Probability Distributions
    • 12  Bernoulli Distribution
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    • 14  Geometric Distribution
    • 15  Negative Binomial Distribution
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    • 17  Multinomial Distribution
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    • 19  Uniform Distribution (Rectangular Distribution)
    • 20  Normal Distribution (Gaussian Distribution)
    • 21  Gaussian Naive Bayes Classifier
    • 22  Chi Distribution
    • 23  Chi-squared Distribution (1 parameter)
    • 24  Chi-squared Distribution (2 parameters)
    • 25  Student t-Distribution
    • 26  Fisher F-Distribution
    • 27  Exponential Distribution
    • 28  Lognormal Distribution
    • 29  Gamma Distribution
    • 30  Beta Distribution
    • 31  Weibull Distribution
    • 32  Pareto Distribution
    • 33  Inverse Gamma Distribution
    • 34  Rayleigh Distribution
    • 35  Erlang Distribution
    • 36  Logistic Distribution
    • 37  Laplace Distribution
    • 38  Gumbel Distribution
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    • 40  Triangular Distribution
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    • 43  Sample Correlation Distribution

    • 44  Problems
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    • 53  Stem-and-Leaf Plot
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    • 78  Equi-distant Time Series
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    • 86  Problems
  • Hypothesis Testing
    • 87  Normal Distributions revisited
    • 88  The Population
    • 89  The Sample
    • 90  The One-Sided Hypothesis Test
    • 91  The Two-Sided Hypothesis Test
    • 92  When to use a one-sided or two-sided test?
    • 93  What if \(\sigma\) is unknown?
    • 94  The Central Limit Theorem (revisited)
    • 95  Statistical Test of the Population Mean with known Variance
    • 96  Statistical Test of the Population Mean with unknown Variance
    • 97  Statistical Test of the Variance
    • 98  Statistical Test of the Population Proportion
    • 99  Statistical Test of the Standard Deviation \(\sigma\)
    • 100  Statistical Test of the difference between Means -- Independent/Unpaired Samples
    • 101  Statistical Test of the difference between Means -- Dependent/Paired Samples
    • 102  Statistical Test of the difference between Variances -- Independent/Unpaired Samples

    • 103  Hypothesis Testing for Research Purposes
    • 104  Decision Thresholds, Alpha, and Confidence Levels
    • 105  Bayesian Inference for Decision-Making
    • 106  One Sample t-Test
    • 107  Skewness & Kurtosis Tests
    • 108  Paired Two Sample t-Test
    • 109  Wilcoxon Signed-Rank Test
    • 110  Unpaired Two Sample t-Test
    • 111  Unpaired Two Sample Welch Test
    • 112  Two One-Sided Tests (TOST) for Equivalence
    • 113  Mann-Whitney U test (Wilcoxon Rank-Sum Test)
    • 114  Bayesian Two Sample Test
    • 115  Median Test based on Notched Boxplots
    • 116  Chi-Squared Tests for Count Data
    • 117  Kolmogorov-Smirnov Test
    • 118  One Way Analysis of Variance (1-way ANOVA)
    • 119  Kruskal-Wallis Test
    • 120  Two Way Analysis of Variance (2-way ANOVA)
    • 121  Repeated Measures ANOVA
    • 122  Friedman Test
    • 123  Testing Correlations
    • 124  A Note on Causality

    • 125  Problems
  • Regression Models
    • 126  Simple Linear Regression Model (SLRM)
    • 127  Multiple Linear Regression Model (MLRM)
    • 128  Logistic Regression
    • 129  Generalized Linear Models
    • 130  Multinomial and Ordinal Logistic Regression
    • 131  Cox Proportional Hazards Regression
    • 132  Conditional Inference Trees
    • 133  Leaf Diagnostics for Conditional Inference Trees
    • 134  Hypothesis Testing with Linear Regression Models (from a Practical Point of View)

    • 135  Problems
  • Introduction to Time Series Analysis
    • 136  Case: the Market of Health and Personal Care Products
    • 137  Decomposition of Time Series
    • 138  Ad hoc Forecasting of Time Series
  • Box-Jenkins Analysis
    • 139  Introduction to Box-Jenkins Analysis
    • 140  Theoretical Concepts
    • 141  Stationarity
    • 142  Identifying ARMA parameters
    • 143  Estimating ARMA Parameters and Residual Diagnostics
    • 144  Forecasting with ARIMA models
    • 145  Intervention Analysis
    • 146  Cross-Correlation Function
    • 147  Transfer Function Noise Models
    • 148  General-to-Specific Modeling
  • References
  • Appendices
    • Appendices
    • A  Method Selection Guide
    • B  Presentations and Teaching Materials
    • C  R Language Concepts for Statistical Computing
    • D  Matrix Algebra
    • E  Standard Normal Table (Gaussian Table)
    • F  Critical values of Student’s \(t\) distribution with \(\nu\) degrees of freedom
    • G  Upper-tail critical values of the \(\chi^2\)-distribution with \(\nu\) degrees of freedom
    • H  Lower-tail critical values of the \(\chi^2\)-distribution with \(\nu\) degrees of freedom
DRAFT This draft is under development — DO NOT CITE OR SHARE.
  1. Appendices
  2. F  Critical values of Student’s \(t\) distribution with \(\nu\) degrees of freedom

Appendix F — Critical values of Student’s \(t\) distribution with \(\nu\) degrees of freedom

The following table displays the critical values \(|c|\), where \(c = t_{1-\alpha, \nu}\) is a quantile of the Student \(t\) distribution with \(\nu\) degrees of freedom and a significance level \(\alpha\): P\((X \leq c) = 1 - \alpha\).

For a symmetric (i.e. two-sided) interval we use the column corresponding to \(1 - \alpha/2\) and the row which is equal to \(\nu = N - K\) (where \(K\) is the number of parameters of the model; in a pooled two-sample \(t\) test, \(\nu = N_1 + N_2 - 2\); Welch’s \(t\) test uses the Welch-Satterthwaite formula for \(\nu\)). For a one-sided test or interval, use the column corresponding to \(1 - \alpha\) directly. For instance, if \(N\) is very large (i.e. \(N - K > 100\), which for the sample mean with \(K = 1\) means \(N > 101\)), the 0.975 column at \(\nu = 100\) gives 1.984, while 1.960 is the limiting value at \(\nu = \infty\) (the Normal Distribution).

Table F.1: Probability less than the critical value \(\left( t_{1-\alpha, \nu} \right)\) – (source: NIST/SEMATECH (n.d.); URL: web page )
\(\nu\) 0.90 0.95 0.975 0.99 0.995 0.999
1 3.078 6.314 12.706 31.821 63.657 318.313
2 1.886 2.920 4.303 6.965 9.925 22.327
3 1.638 2.353 3.182 4.541 5.841 10.215
4 1.533 2.132 2.776 3.747 4.604 7.173
5 1.476 2.015 2.571 3.365 4.032 5.893
6 1.440 1.943 2.447 3.143 3.707 5.208
7 1.415 1.895 2.365 2.998 3.499 4.782
8 1.397 1.860 2.306 2.896 3.355 4.499
9 1.383 1.833 2.262 2.821 3.250 4.296
10 1.372 1.812 2.228 2.764 3.169 4.143
11 1.363 1.796 2.201 2.718 3.106 4.024
12 1.356 1.782 2.179 2.681 3.055 3.929
13 1.350 1.771 2.160 2.650 3.012 3.852
14 1.345 1.761 2.145 2.624 2.977 3.787
15 1.341 1.753 2.131 2.602 2.947 3.733
16 1.337 1.746 2.120 2.583 2.921 3.686
17 1.333 1.740 2.110 2.567 2.898 3.646
18 1.330 1.734 2.101 2.552 2.878 3.610
19 1.328 1.729 2.093 2.539 2.861 3.579
20 1.325 1.725 2.086 2.528 2.845 3.552
21 1.323 1.721 2.080 2.518 2.831 3.527
22 1.321 1.717 2.074 2.508 2.819 3.505
23 1.319 1.714 2.069 2.500 2.807 3.485
24 1.318 1.711 2.064 2.492 2.797 3.467
25 1.316 1.708 2.060 2.485 2.787 3.450
26 1.315 1.706 2.056 2.479 2.779 3.435
27 1.314 1.703 2.052 2.473 2.771 3.421
28 1.313 1.701 2.048 2.467 2.763 3.408
29 1.311 1.699 2.045 2.462 2.756 3.396
30 1.310 1.697 2.042 2.457 2.750 3.385
31 1.309 1.696 2.040 2.453 2.744 3.375
32 1.309 1.694 2.037 2.449 2.738 3.365
33 1.308 1.692 2.035 2.445 2.733 3.356
34 1.307 1.691 2.032 2.441 2.728 3.348
35 1.306 1.690 2.030 2.438 2.724 3.340
36 1.306 1.688 2.028 2.434 2.719 3.333
37 1.305 1.687 2.026 2.431 2.715 3.326
38 1.304 1.686 2.024 2.429 2.712 3.319
39 1.304 1.685 2.023 2.426 2.708 3.313
40 1.303 1.684 2.021 2.423 2.704 3.307
41 1.303 1.683 2.020 2.421 2.701 3.301
42 1.302 1.682 2.018 2.418 2.698 3.296
43 1.302 1.681 2.017 2.416 2.695 3.291
44 1.301 1.680 2.015 2.414 2.692 3.286
45 1.301 1.679 2.014 2.412 2.690 3.281
46 1.300 1.679 2.013 2.410 2.687 3.277
47 1.300 1.678 2.012 2.408 2.685 3.273
48 1.299 1.677 2.011 2.407 2.682 3.269
49 1.299 1.677 2.010 2.405 2.680 3.265
50 1.299 1.676 2.009 2.403 2.678 3.261
51 1.298 1.675 2.008 2.402 2.676 3.258
52 1.298 1.675 2.007 2.400 2.674 3.255
53 1.298 1.674 2.006 2.399 2.672 3.251
54 1.297 1.674 2.005 2.397 2.670 3.248
55 1.297 1.673 2.004 2.396 2.668 3.245
56 1.297 1.673 2.003 2.395 2.667 3.242
57 1.297 1.672 2.002 2.394 2.665 3.239
58 1.296 1.672 2.002 2.392 2.663 3.237
59 1.296 1.671 2.001 2.391 2.662 3.234
60 1.296 1.671 2.000 2.390 2.660 3.232
61 1.296 1.670 2.000 2.389 2.659 3.229
62 1.295 1.670 1.999 2.388 2.657 3.227
63 1.295 1.669 1.998 2.387 2.656 3.225
64 1.295 1.669 1.998 2.386 2.655 3.223
65 1.295 1.669 1.997 2.385 2.654 3.220
66 1.295 1.668 1.997 2.384 2.652 3.218
67 1.294 1.668 1.996 2.383 2.651 3.216
68 1.294 1.668 1.995 2.382 2.650 3.214
69 1.294 1.667 1.995 2.382 2.649 3.213
70 1.294 1.667 1.994 2.381 2.648 3.211
71 1.294 1.667 1.994 2.380 2.647 3.209
72 1.293 1.666 1.993 2.379 2.646 3.207
73 1.293 1.666 1.993 2.379 2.645 3.206
74 1.293 1.666 1.993 2.378 2.644 3.204
75 1.293 1.665 1.992 2.377 2.643 3.202
76 1.293 1.665 1.992 2.376 2.642 3.201
77 1.293 1.665 1.991 2.376 2.641 3.199
78 1.292 1.665 1.991 2.375 2.640 3.198
79 1.292 1.664 1.990 2.374 2.640 3.197
80 1.292 1.664 1.990 2.374 2.639 3.195
81 1.292 1.664 1.990 2.373 2.638 3.194
82 1.292 1.664 1.989 2.373 2.637 3.193
83 1.292 1.663 1.989 2.372 2.636 3.191
84 1.292 1.663 1.989 2.372 2.636 3.190
85 1.292 1.663 1.988 2.371 2.635 3.189
86 1.291 1.663 1.988 2.370 2.634 3.188
87 1.291 1.663 1.988 2.370 2.634 3.187
88 1.291 1.662 1.987 2.369 2.633 3.185
89 1.291 1.662 1.987 2.369 2.632 3.184
90 1.291 1.662 1.987 2.368 2.632 3.183
91 1.291 1.662 1.986 2.368 2.631 3.182
92 1.291 1.662 1.986 2.368 2.630 3.181
93 1.291 1.661 1.986 2.367 2.630 3.180
94 1.291 1.661 1.986 2.367 2.629 3.179
95 1.291 1.661 1.985 2.366 2.629 3.178
96 1.290 1.661 1.985 2.366 2.628 3.177
97 1.290 1.661 1.985 2.365 2.627 3.176
98 1.290 1.661 1.984 2.365 2.627 3.175
99 1.290 1.660 1.984 2.365 2.626 3.175
100 1.290 1.660 1.984 2.364 2.626 3.174
\(\infty\) 1.282 1.645 1.960 2.326 2.576 3.090
NIST/SEMATECH. n.d. E-Handbook of Statistical Methods. NIST/SEMATECH. http://www.itl.nist.gov/div898/handbook/.
E  Standard Normal Table (Gaussian Table)
G  Upper-tail critical values of the \(\chi^2\)-distribution with \(\nu\) degrees of freedom

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