RAR-files |
p-0133578860.rar |
100,000,000 |
69C3092E |
p-0133578860.r00 |
100,000,000 |
29083218 |
p-0133578860.r01 |
100,000,000 |
F5F408F4 |
p-0133578860.r02 |
100,000,000 |
7C04956E |
p-0133578860.r03 |
100,000,000 |
12B9C191 |
p-0133578860.r04 |
100,000,000 |
0DA76661 |
p-0133578860.r05 |
100,000,000 |
AFFBA4FC |
p-0133578860.r06 |
100,000,000 |
210CBBBA |
p-0133578860.r07 |
100,000,000 |
39531C0A |
p-0133578860.r08 |
100,000,000 |
DEA27E86 |
p-0133578860.r09 |
100,000,000 |
ED410182 |
p-0133578860.r10 |
100,000,000 |
365D43EE |
p-0133578860.r11 |
100,000,000 |
EDA8652B |
p-0133578860.r12 |
100,000,000 |
8A77729F |
p-0133578860.r13 |
100,000,000 |
081005DC |
p-0133578860.r14 |
100,000,000 |
A6364175 |
p-0133578860.r15 |
100,000,000 |
87C310E1 |
p-0133578860.r16 |
100,000,000 |
DADBBBD1 |
p-0133578860.r17 |
100,000,000 |
4387D16E |
p-0133578860.r18 |
100,000,000 |
30BE098F |
p-0133578860.r19 |
100,000,000 |
5EB64046 |
p-0133578860.r20 |
100,000,000 |
B947E46D |
p-0133578860.r21 |
100,000,000 |
61286928 |
p-0133578860.r22 |
100,000,000 |
4958C02F |
p-0133578860.r23 |
100,000,000 |
998CE4FC |
p-0133578860.r24 |
100,000,000 |
30FCE45C |
p-0133578860.r25 |
100,000,000 |
2FBB3E97 |
p-0133578860.r26 |
100,000,000 |
89E0D941 |
p-0133578860.r27 |
100,000,000 |
0553BE1B |
p-0133578860.r28 |
100,000,000 |
B49DD91E |
p-0133578860.r29 |
100,000,000 |
C4C02F5E |
p-0133578860.r30 |
100,000,000 |
0C814611 |
p-0133578860.r31 |
100,000,000 |
12943EA3 |
p-0133578860.r32 |
100,000,000 |
10166BF8 |
p-0133578860.r33 |
100,000,000 |
AE87B9E3 |
p-0133578860.r34 |
100,000,000 |
45DD846F |
p-0133578860.r35 |
100,000,000 |
6119353A |
p-0133578860.r36 |
100,000,000 |
A230FD10 |
p-0133578860.r37 |
100,000,000 |
D7C79644 |
p-0133578860.r38 |
100,000,000 |
1586837F |
p-0133578860.r39 |
100,000,000 |
C2F318E3 |
p-0133578860.r40 |
100,000,000 |
771B3274 |
p-0133578860.r41 |
100,000,000 |
1821F66D |
p-0133578860.r42 |
100,000,000 |
B3BE06BF |
p-0133578860.r43 |
100,000,000 |
E730F016 |
p-0133578860.r44 |
100,000,000 |
19D3947A |
p-0133578860.r45 |
100,000,000 |
C1D4B37C |
p-0133578860.r46 |
100,000,000 |
D7DE768C |
p-0133578860.r47 |
100,000,000 |
4933B037 |
p-0133578860.r48 |
100,000,000 |
C723AA9E |
p-0133578860.r49 |
100,000,000 |
2C97C01F |
p-0133578860.r50 |
100,000,000 |
A9269FD9 |
p-0133578860.r51 |
100,000,000 |
4FC394E1 |
p-0133578860.r52 |
100,000,000 |
3C1CBA05 |
p-0133578860.r53 |
100,000,000 |
FA3F8F7D |
p-0133578860.r54 |
100,000,000 |
A26648DE |
p-0133578860.r55 |
100,000,000 |
6C83E3FC |
p-0133578860.r56 |
100,000,000 |
BF808F32 |
p-0133578860.r57 |
100,000,000 |
84F32DEB |
p-0133578860.r58 |
100,000,000 |
9AE0AD91 |
p-0133578860.r59 |
100,000,000 |
0A13AD1D |
p-0133578860.r60 |
100,000,000 |
FCF26EB8 |
p-0133578860.r61 |
100,000,000 |
2798CE8B |
p-0133578860.r62 |
100,000,000 |
5503A081 |
p-0133578860.r63 |
100,000,000 |
529BC952 |
p-0133578860.r64 |
100,000,000 |
B8DDBC5E |
p-0133578860.r65 |
100,000,000 |
8645F06B |
p-0133578860.r66 |
100,000,000 |
2204A47E |
p-0133578860.r67 |
100,000,000 |
AC81D480 |
p-0133578860.r68 |
100,000,000 |
645A62CA |
p-0133578860.r69 |
100,000,000 |
8F2B7970 |
p-0133578860.r70 |
100,000,000 |
820AFDA7 |
p-0133578860.r71 |
100,000,000 |
2A027990 |
p-0133578860.r72 |
100,000,000 |
7D9AA3FA |
p-0133578860.r73 |
100,000,000 |
FB3C298F |
p-0133578860.r74 |
100,000,000 |
432D5BEC |
p-0133578860.r75 |
100,000,000 |
F2B69D5A |
p-0133578860.r76 |
100,000,000 |
C9B4847E |
p-0133578860.r77 |
100,000,000 |
4553AC6D |
p-0133578860.r78 |
100,000,000 |
EBE10CCE |
p-0133578860.r79 |
100,000,000 |
D9CE0539 |
p-0133578860.r80 |
100,000,000 |
23B4014D |
p-0133578860.r81 |
100,000,000 |
8224B51F |
p-0133578860.r82 |
100,000,000 |
ABA7A276 |
p-0133578860.r83 |
100,000,000 |
AB7EB18C |
p-0133578860.r84 |
100,000,000 |
6437B6C4 |
p-0133578860.r85 |
17,218,168 |
21D317CE |
|
Total size: |
8,617,218,168 |
|
|
Archived
files |
Introduction |
0 |
00000000 |
Introduction\0 - Introduction to R Programming LiveLessons.mp4
[54f1e6b9167e9aea]
|
185,142,123 |
856A02D0 |
Lesson 10: Linear Models |
0 |
00000000 |
Lesson 10: Linear Models\6 - 10.6 Analyze survival data.mp4
[f54b12516993eeb4]
|
190,820,985 |
DE2DB0FD |
Lesson 10: Linear Models\10 - 10.10 Estimate uncertainty with the bootstrap.mp4
[bc8ce04750bb5b60]
|
96,075,309 |
5AB560F4 |
Lesson 10: Linear Models\8 - 10.8 Compare models.mp4
[29c5864ffe9c0c9d]
|
129,213,259 |
6D5A4DB3 |
Lesson 10: Linear Models\7 - 10.7 Assess model quality with residuals.mp4
[78b00aff5bc6f11]
|
101,950,802 |
1AC2E8ED |
Lesson 10: Linear Models\11 - 10.11 Choose variables using stepwise selection.mp4
[24781c10b95d80dd]
|
53,184,694 |
B275E4B2 |
Lesson 10: Linear Models\0 - Learning objectives.mp4
[c668c7ded64f9d21]
|
21,803,002 |
899638F8 |
Lesson 10: Linear Models\2 - 10.2 Explore the data.mp4
[e03f701d33490414]
|
206,400,892 |
9B551884 |
Lesson 10: Linear Models\4 - 10.4 Fit logistic regression.mp4
[11abcf7e7f0f89c3]
|
156,019,816 |
31F4C52E |
Lesson 10: Linear Models\5 - 10.5 Fit Poisson regression.mp4
[9d4a668ab6d8348e]
|
104,446,603 |
FD1FA01F |
Lesson 10: Linear Models\9 - 10.9 Judge accuracy using cross-validation.mp4
[b945f867edd5d50f]
|
148,709,521 |
9B60E9F0 |
Lesson 10: Linear Models\1 - 10.1 Fit simple linear models.mp4
[84ddbf997e2573b6]
|
147,079,270 |
406CFE43 |
Lesson 10: Linear Models\3 - 10.3 Fit multiple regression models.mp4
[c13b31009114e7e5]
|
333,189,765 |
B8E91929 |
Lesson 11: Other Models |
0 |
00000000 |
Lesson 11: Other Models\1 - 11.1 Select variables and improve predictions with the elastic net.mp4
[68b685e3c5803283]
|
224,830,557 |
C176C67D |
Lesson 11: Other Models\4 - 11.4 Splines.mp4
[5fe1cbcc46c5dc60]
|
126,480,635 |
BB1096E5 |
Lesson 11: Other Models\0 - Learning objectives.mp4
[bb3f549047ce131d]
|
22,286,948 |
4713CC47 |
Lesson 11: Other Models\6 - 11.6 Fit decision trees to make a random forest.mp4
[8f7ba9a59eed4008]
|
90,457,181 |
29BC5621 |
Lesson 11: Other Models\5 - 11.5 GAMs.mp4
[f243dae84141475a]
|
96,425,766 |
1B1F190C |
Lesson 11: Other Models\2 - 11.2 Decrease uncertainty with weakly informative priors.mp4
[f562927373f43bad]
|
157,364,989 |
BA2C3BDA |
Lesson 11: Other Models\3 - 11.3 Fit nonlinear least squares.mp4
[a259f7c3f237fa48]
|
81,113,310 |
50DB2CDC |
Lesson 12: Time Series |
0 |
00000000 |
Lesson 12: Time Series\2 - 12.2 Fit and assess ARIMA models.mp4
[d982c2bb7d375e4a]
|
52,639,408 |
50E537C6 |
Lesson 12: Time Series\4 - 12.4 Use GARCH for better volatility modeling.mp4
[5a4be845244d2592]
|
173,023,027 |
1E140AF7 |
Lesson 12: Time Series\0 - Learning objectives.mp4
[ad29862e0336a6a3]
|
16,543,873 |
85CB04DF |
Lesson 12: Time Series\1 - 12.1 Understand ACF and PACF.mp4
[75bb8fae173e5824]
|
124,852,045 |
B39C9D4C |
Lesson 13: Clustering |
0 |
00000000 |
Lesson 13: Clustering\0 - Learning objectives.mp4
[d16f53aae1c8e56e]
|
15,945,152 |
D1118A09 |
Lesson 13: Clustering\1 - 13.1: Partition data with K-means.mp4
[3a9ac7640e7b1a9]
|
205,243,628 |
2FAB77C8 |
Lesson 13: Clustering\3 - 13.3: Perform hierarchical clustering.mp4
[b1ec1f648f375d98]
|
82,760,547 |
7961F1CA |
Lesson 13: Clustering\2 - 13.2: Robustly cluster, even with categorical data, with PAM.mp4
[25b81a5359132da4]
|
24,255,336 |
E354AAF1 |
Lesson 14: Reports and Slideshows with knitr |
0 |
00000000 |
Lesson 14: Reports and Slideshows with knitr\3 - 14.3: Understand the basics of Markdown.mp4
[b6136be0e2df1d94]
|
26,190,913 |
CD44F7D8 |
Lesson 14: Reports and Slideshows with knitr\2 - 14.2: Weave R code into LaTeX using knitr.mp4
[58741b582c2fe475]
|
77,118,901 |
E8140EE3 |
Lesson 14: Reports and Slideshows with knitr\0 - Learning objectives.mp4
[ff02508e98d73f7]
|
24,614,911 |
0387FD8E |
Lesson 14: Reports and Slideshows with knitr\1 - 14.1: Understand the basics of LaTeX.mp4
[43e1ed91a2c74286]
|
81,124,455 |
5D0A0E75 |
Lesson 14: Reports and Slideshows with knitr\5 - 14.5: Use pandoc to convert from Markdown to HTML5 slideshow.mp4
[4d8f2f071c3dc2b6]
|
68,213,191 |
998DE428 |
Lesson 14: Reports and Slideshows with knitr\4 - 14.4: Weave R code into Markdown using knitr.mp4
[eeb6db68f5dc5ce5]
|
32,317,067 |
7561786A |
Lesson 15: Package Building |
0 |
00000000 |
Lesson 15: Package Building\4 - 15.4: Submit a package to CRAN.mp4
[d5fe1b61e2b520dc]
|
10,856,913 |
8D750C23 |
Lesson 15: Package Building\2 - 15.2: Write and document functions.mp4
[4c74c6b022124699]
|
135,317,890 |
86ABDFD8 |
Lesson 15: Package Building\0 - Learning objectives.mp4
[763aca367000a7cc]
|
18,413,798 |
3F246AEE |
Lesson 15: Package Building\3 - 15.3: Check and build a package.mp4
[504bef0a281e6d78]
|
44,575,542 |
6672AFAC |
Lesson 15: Package Building\1 - 15.1: Understand the folder structure and files in a package.mp4
[74e1f0d244be6742]
|
84,868,259 |
46640960 |
Lesson 1: Getting Started with R |
0 |
00000000 |
Lesson 1: Getting Started with R\1 - 1.1 Download and install R.mp4
[1757109b769ae86f]
|
81,308,897 |
CB270072 |
Lesson 1: Getting Started with R\0 - Learning objectives.mp4
[14ed774cc7514fbe]
|
23,170,399 |
7A686EE4 |
Lesson 1: Getting Started with R\2 - 1.2 Work in The R environment.mp4
[e4e845fc58d96c9b]
|
257,280,213 |
1A5E295B |
Lesson 1: Getting Started with R\3 - 1.3 Install and load packages.mp4
[fccf2e7aea83b866]
|
99,929,022 |
392B182A |
Lesson 2: The Basic Building Blocks in R |
0 |
00000000 |
Lesson 2: The Basic Building Blocks in R\1 - 2.1 Use R as a calculator.mp4
[ea37e5b0fbf8c603]
|
10,505,757 |
E864990B |
Lesson 2: The Basic Building Blocks in R\5 - 2.5 Call functions.mp4
[40eee99eaf6d0447]
|
36,001,403 |
25E50E58 |
Lesson 2: The Basic Building Blocks in R\0 - Learning objectives.mp4
[ab8f7c3e963be432]
|
22,436,565 |
FD1B2239 |
Lesson 2: The Basic Building Blocks in R\2 - 2.2 Work with variables.mp4
[dd84e24b24fcd8cc]
|
40,276,053 |
E6F4B5D8 |
Lesson 2: The Basic Building Blocks in R\4 - 2.4 Store data in vectors.mp4
[dec20e9efc426e77]
|
224,954,475 |
1863D0E2 |
Lesson 3: Advanced Data Structures in R |
0 |
00000000 |
Lesson 3: Advanced Data Structures in R\1 - 3.1 Create and access information in data.frames.mp4
[8b248179d2fc0629]
|
183,768,373 |
D8FB79C0 |
Lesson 3: Advanced Data Structures in R\0 - Learning objectives.mp4
[8d423561073846d4]
|
20,336,505 |
7D1E5DF0 |
Lesson 3: Advanced Data Structures in R\3 - 3.3 Create and access information in matrices.mp4
[6b3f978a12863bef]
|
78,932,136 |
CF066A43 |
Lesson 3: Advanced Data Structures in R\2 - 3.2 Create and access information in lists.mp4
[b68c44641eba6723]
|
101,416,180 |
501E45BF |
Lesson 3: Advanced Data Structures in R\4 - 3.4 Create and access information in arrays.mp4
[a0dcc9aad114adf5]
|
20,810,053 |
47660344 |
Lesson 4: Reading Data into R |
0 |
00000000 |
Lesson 4: Reading Data into R\6 - 4.6 Load data included with R.mp4
[cc72d44006e9e6b8]
|
31,170,727 |
2DB97623 |
Lesson 4: Reading Data into R\0 - Learning objectives.mp4
[6a0666edf3319d5d]
|
19,521,957 |
79714BF8 |
Lesson 4: Reading Data into R\3 - 4.3 Read from databases.mp4
[e979d3d2d14ce85e]
|
79,384,211 |
F0E56FFA |
Lesson 4: Reading Data into R\1 - 4.1 Read a CSV into R.mp4
[b29233aaf5908c65]
|
88,316,530 |
591BB78D |
Lesson 4: Reading Data into R\2 - 4.2 Understand that Excel is not easily readable into R.mp4
[c4ef888fc558c236]
|
38,395,806 |
62039F0F |
Lesson 4: Reading Data into R\5 - 4.5 Load binary R files.mp4
[b037c3934aed4254]
|
62,498,004 |
B0AFFD0B |
Lesson 4: Reading Data into R\4 - 4.4 Read data files from other statistical tools.mp4
[a4b7f6854eb32b1c]
|
12,534,844 |
075E4540 |
Lesson 4: Reading Data into R\7 - 4.7 Scrape data from the web.mp4
[d292cb1ea5fd1c45]
|
32,833,547 |
D47875DE |
Lesson 5: Making Statistical Graphs |
0 |
00000000 |
Lesson 5: Making Statistical Graphs\1 - 5.1 Find the diamonds data.mp4.part
[3ca30d0c691e215e]
|
11,786,024 |
1305E5FC |
Lesson 5: Making Statistical Graphs\9 - 5.9 Make line plots.mp4
[ba0888c2e94dce5]
|
117,418,586 |
63364BE4 |
Lesson 5: Making Statistical Graphs\8 - 5.8 Make boxplots and violin plots with ggplot2.mp4
[85a4a16a3c16a3eb]
|
57,704,466 |
968A6233 |
Lesson 5: Making Statistical Graphs\6 - 5.6 Plot histograms and densities with ggplot2.mp4
[58414819ccfcd96]
|
36,343,522 |
0CF16F0D |
Lesson 5: Making Statistical Graphs\0 - Learning objectives.mp4
[3b93fb8a131578e]
|
23,803,188 |
7FF64041 |
Lesson 5: Making Statistical Graphs\3 - 5.3 Make scatterplots with base graphics.mp4
[d7e92439861a170]
|
17,966,616 |
2D27A596 |
Lesson 5: Making Statistical Graphs\12 - 5.12 Add themes to graphs.mp4
[6a83001b3b5b76c0]
|
29,122,100 |
D1BB2B05 |
Lesson 5: Making Statistical Graphs\10 - 5.10 Create small multiples.mp4
[a72ffa05b771691d]
|
62,030,737 |
604500F9 |
Lesson 5: Making Statistical Graphs\2 - 5.2 Make histograms with base graphics.mp4
[75fe9921c80a0f5d]
|
12,904,141 |
BCBA828C |
Lesson 5: Making Statistical Graphs\5 - 5.5 Get familiar with ggplot2.mp4
[c294691c956645dc]
|
20,617,546 |
B3B0CA92 |
Lesson 5: Making Statistical Graphs\4 - 5.4 Make boxplots with base graphics.mp4
[620d718bd1067c49]
|
9,301,347 |
E382FBF5 |
Lesson 5: Making Statistical Graphs\7 - 5.7 Make scatterplots with ggplot2.mp4
[c8767509af749896]
|
63,257,101 |
A4EC344C |
Lesson 5: Making Statistical Graphs\11 - 5.11 Control colors and shapes.mp4
[f71bd131afd1597e]
|
17,195,959 |
8BFD6D9A |
Lesson 6: Basics of Programming |
0 |
00000000 |
Lesson 6: Basics of Programming\7 - 6.7 Check multiple statements with switch.mp4
[e4021d3e3d55b756]
|
37,485,859 |
9FDA454D |
Lesson 6: Basics of Programming\2 - 6.2 Understand the basics of function arguments.mp4
[232e45ca4f3ea47c]
|
109,781,321 |
92E8CCE5 |
Lesson 6: Basics of Programming\10 - 6.10 Iterate with a for loop.mp4
[5b6549e5f818b32b]
|
57,873,164 |
168E9023 |
Lesson 6: Basics of Programming\3 - 6.3 Return a value from a function.mp4
[2055c26712624f4a]
|
23,781,597 |
3C89DAF9 |
Lesson 6: Basics of Programming\0 - Learning objectives.mp4
[d4971e757b212831]
|
22,569,566 |
C7AF00AB |
Lesson 6: Basics of Programming\6 - 6.6 Stagger if statements with else.mp4
[5ee375fc3a95f93e]
|
51,150,217 |
FE331053 |
Lesson 6: Basics of Programming\5 - 6.5 Use if statements to control program flow.mp4
[3d753bcde6392c53]
|
15,670,125 |
EBBE3DBA |
Lesson 6: Basics of Programming\12 - 6.12 Control loops with break and next.mp4
[9bef524fef033be8]
|
15,451,958 |
8015CF7E |
Lesson 6: Basics of Programming\4 - 6.4 Gain flexibility with do.call.mp4
[855678c1b0f01201]
|
38,932,346 |
D2BE7B90 |
Lesson 6: Basics of Programming\8 - 6.8 Run checks on entire vectors.mp4
[15c961497779c1a2]
|
52,892,434 |
A35FE090 |
Lesson 6: Basics of Programming\9 - 6.9 Check compound statements.mp4
[684d303c75d0fa59]
|
48,123,336 |
7FBA28A9 |
Lesson 6: Basics of Programming\11 - 6.11 Iterate with a while loop.mp4
[a78b11569e420436]
|
10,368,919 |
B5A80067 |
Lesson 7: Data Munging |
0 |
00000000 |
Lesson 7: Data Munging\6 - 7.6 Combine datasets.mp4
[3a892355dea92dc7]
|
60,986,545 |
662788D5 |
Lesson 7: Data Munging\5 - 7.5 The plyr package.mp4
[c1dada94a03d4f05]
|
297,132,857 |
A94B2C29 |
Lesson 7: Data Munging\3 - 7.3 The mapply.mp4
[a7ac4a79e0c6cffa]
|
46,352,039 |
FF518E3B |
Lesson 7: Data Munging\4 - 7.4 The aggregate function.mp4
[396c39893acf2218]
|
84,441,141 |
27E9966A |
Lesson 7: Data Munging\7 - 7.7 Join datasets.mp4
[a99903cf5aec59d1]
|
79,962,896 |
91C584E0 |
Lesson 7: Data Munging\0 - Learning objectives.mp4
[5ea27b0cb2dd58ac]
|
25,294,542 |
D51F8758 |
Lesson 7: Data Munging\1 - 7.1 Repeat an operation on a matrix using apply.mp4
[69a09bc7caa34dc4]
|
48,971,605 |
54B14DF2 |
Lesson 7: Data Munging\2 - 7.2 Repeat an operation on a list.mp4
[5617eb114fc96a43]
|
23,952,331 |
C73D9156 |
Lesson 7: Data Munging\8 - 7.8 Switch storage paradigms.mp4
[af731c2f79f5b62c]
|
69,123,765 |
C04F9EA3 |
Lesson 8: Manipulating Strings |
0 |
00000000 |
Lesson 8: Manipulating Strings\2 - 8.2 Extract text.mp4
[352b5add51962fb4]
|
518,450,757 |
B7904E06 |
Lesson 8: Manipulating Strings\0 - Learning objectives.mp4
[74c244bcce7321d9]
|
16,470,428 |
D6549413 |
Lesson 8: Manipulating Strings\1 - 8.1 Combine strings together.mp4
[32e5df5d6e86adf6]
|
132,795,643 |
1D614A78 |
Lesson 9: Basic Statistics |
0 |
00000000 |
Lesson 9: Basic Statistics\0 - Learning objectives.mp4
[e9021fe15d5bf611]
|
16,326,465 |
C90C3005 |
Lesson 9: Basic Statistics\1 - 9.1: Draw numbers from probability distributions.mp4
[815fb0d6f881532c]
|
338,494,537 |
B98D2CE9 |
Lesson 9: Basic Statistics\2 - 9.2: Calculate averages, standard deviations and correlations.mp4
[d7cf1783ce3f4504]
|
8,247,122 |
60BF5A71 |
Lesson 9: Basic Statistics\3 - 9.3: Compare samples with t-tests and analysis of variance.mp4
[78646738a23ef81f]
|
285,951,533 |
52695B32 |
Summary |
0 |
00000000 |
Summary\0 - Summary of R Programming LiveLessons.mp4
[36583f4f1cb2a4a9]
|
63,057,107 |
8D6F0D7C |
|
Total size: |
8,617,195,428 |
|
|