Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Beijing
O'Reilly
May 2020
|
| Ausgabe: | Second edition |
| Schlagwörter: | |
| Links: | https://ebookcentral.proquest.com/lib/th-ab/detail.action?docID=6173908 https://ebookcentral.proquest.com/lib/th-deggendorf/detail.action?docID=6173908 https://ebookcentral.proquest.com/lib/uniregensburg-ebooks/detail.action?docID=6173908 https://ebookcentral.proquest.com/lib/erlangen/detail.action?docID=6173908 |
| Umfang: | 1 Online-Ressource (xvi, 342 Seiten) |
| ISBN: | 9781492072911 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV046803637 | ||
| 003 | DE-604 | ||
| 005 | 20230801 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 200713s2020 xx o|||| 00||| eng d | ||
| 020 | |a 9781492072911 |c online |9 978-1-492-07291-1 | ||
| 035 | |a (OCoLC)1190674899 | ||
| 035 | |a (DE-599)BVBBV046803637 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-1050 |a DE-1043 |a DE-355 |a DE-29 | ||
| 084 | |a SK 850 |0 (DE-625)143263: |2 rvk | ||
| 084 | |a ST 250 |0 (DE-625)143626: |2 rvk | ||
| 084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
| 084 | |a ST 530 |0 (DE-625)143679: |2 rvk | ||
| 100 | 1 | |a Bruce, Peter C. |d 1953- |e Verfasser |0 (DE-588)1104275260 |4 aut | |
| 245 | 1 | 0 | |a Practical statistics for data scientists |b 50+ essential concepts using R and Python |c Peter Bruce, Andrew Bruce, and Peter Gedeck |
| 250 | |a Second edition | ||
| 264 | 1 | |a Beijing |b O'Reilly |c May 2020 | |
| 300 | |a 1 Online-Ressource (xvi, 342 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 505 | 8 | |a Cover -- Copyright -- Table of Contents -- Preface -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. Exploratory Data Analysis -- Elements of Structured Data -- Further Reading -- Rectangular Data -- Data Frames and Indexes -- Nonrectangular Data Structures -- Further Reading -- Estimates of Location -- Mean -- Median and Robust Estimates -- Example: Location Estimates of Population and Murder Rates -- Further Reading -- Estimates of Variability -- Standard Deviation and Related Estimates | |
| 505 | 8 | |a Estimates Based on Percentiles -- Example: Variability Estimates of State Population -- Further Reading -- Exploring the Data Distribution -- Percentiles and Boxplots -- Frequency Tables and Histograms -- Density Plots and Estimates -- Further Reading -- Exploring Binary and Categorical Data -- Mode -- Expected Value -- Probability -- Further Reading -- Correlation -- Scatterplots -- Further Reading -- Exploring Two or More Variables -- Hexagonal Binning and Contours (Plotting Numeric Versus Numeric Data) -- Two Categorical Variables -- Categorical and Numeric Data | |
| 505 | 8 | |a Visualizing Multiple Variables -- Further Reading -- Summary -- Chapter 2. Data and Sampling Distributions -- Random Sampling and Sample Bias -- Bias -- Random Selection -- Size Versus Quality: When Does Size Matter? -- Sample Mean Versus Population Mean -- Further Reading -- Selection Bias -- Regression to the Mean -- Further Reading -- Sampling Distribution of a Statistic -- Central Limit Theorem -- Standard Error -- Further Reading -- The Bootstrap -- Resampling Versus Bootstrapping -- Further Reading -- Confidence Intervals -- Further Reading -- Normal Distribution | |
| 505 | 8 | |a Standard Normal and QQ-Plots -- Long-Tailed Distributions -- Further Reading -- Student's t-Distribution -- Further Reading -- Binomial Distribution -- Further Reading -- Chi-Square Distribution -- Further Reading -- F-Distribution -- Further Reading -- Poisson and Related Distributions -- Poisson Distributions -- Exponential Distribution -- Estimating the Failure Rate -- Weibull Distribution -- Further Reading -- Summary -- Chapter 3. Statistical Experiments and Significance Testing -- A/B Testing -- Why Have a Control Group? -- Why Just A/B? Why Not C, D,...? -- Further Reading | |
| 505 | 8 | |a Hypothesis Tests -- The Null Hypothesis -- Alternative Hypothesis -- One-Way Versus Two-Way Hypothesis Tests -- Further Reading -- Resampling -- Permutation Test -- Example: Web Stickiness -- Exhaustive and Bootstrap Permutation Tests -- Permutation Tests: The Bottom Line for Data Science -- Further Reading -- Statistical Significance and p-Values -- p-Value -- Alpha -- Type 1 and Type 2 Errors -- Data Science and p-Values -- Further Reading -- t-Tests -- Further Reading -- Multiple Testing -- Further Reading -- Degrees of Freedom -- Further Reading -- ANOVA -- F-Statistic -- Two-Way ANOVA | |
| 650 | 4 | |a Mathematical analysis / Statistical methods | |
| 650 | 4 | |a Quantitative research / Statistical methods | |
| 650 | 4 | |a Big data / Mathematics | |
| 650 | 0 | 7 | |a Big Data |0 (DE-588)4802620-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Data Mining |0 (DE-588)4428654-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Python |g Programmiersprache |0 (DE-588)4434275-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Datenanalyse |0 (DE-588)4123037-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Data Science |0 (DE-588)1140936166 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Statistik |0 (DE-588)4056995-0 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Data Science |0 (DE-588)1140936166 |D s |
| 689 | 0 | 1 | |a Big Data |0 (DE-588)4802620-7 |D s |
| 689 | 0 | 2 | |a Statistik |0 (DE-588)4056995-0 |D s |
| 689 | 0 | 3 | |a Datenanalyse |0 (DE-588)4123037-1 |D s |
| 689 | 0 | 4 | |a Python |g Programmiersprache |0 (DE-588)4434275-5 |D s |
| 689 | 0 | 5 | |a R |g Programm |0 (DE-588)4705956-4 |D s |
| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Data Mining |0 (DE-588)4428654-5 |D s |
| 689 | 1 | |5 DE-604 | |
| 700 | 1 | |a Bruce, Andrew |e Verfasser |0 (DE-588)170744183 |4 aut | |
| 700 | 1 | |a Gedeck, Peter |e Verfasser |0 (DE-588)1231483199 |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-492-07294-2 |
| 912 | |a ZDB-30-PQE | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-032212322 | |
| 966 | e | |u https://ebookcentral.proquest.com/lib/th-ab/detail.action?docID=6173908 |l DE-1043 |p ZDB-30-PQE |x Aggregator |3 Volltext | |
| 966 | e | |u https://ebookcentral.proquest.com/lib/th-deggendorf/detail.action?docID=6173908 |l DE-1050 |p ZDB-30-PQE |q FHD01_PQE_Kauf |x Aggregator |3 Volltext | |
| 966 | e | |u https://ebookcentral.proquest.com/lib/uniregensburg-ebooks/detail.action?docID=6173908 |l DE-355 |p ZDB-30-PQE |q UBR Sammelbestellung 2021 |x Aggregator |3 Volltext | |
| 966 | e | |u https://ebookcentral.proquest.com/lib/erlangen/detail.action?docID=6173908 |l DE-29 |p ZDB-30-PQE |q UER_Einzelkauf |x Aggregator |3 Volltext | |
Datensatz im Suchindex
| DE-BY-UBR_katkey | 6439940 |
|---|---|
| _version_ | 1835101702816006145 |
| adam_text | |
| any_adam_object | |
| author | Bruce, Peter C. 1953- Bruce, Andrew Gedeck, Peter |
| author_GND | (DE-588)1104275260 (DE-588)170744183 (DE-588)1231483199 |
| author_facet | Bruce, Peter C. 1953- Bruce, Andrew Gedeck, Peter |
| author_role | aut aut aut |
| author_sort | Bruce, Peter C. 1953- |
| author_variant | p c b pc pcb a b ab p g pg |
| building | Verbundindex |
| bvnumber | BV046803637 |
| classification_rvk | SK 850 ST 250 ST 300 ST 530 |
| collection | ZDB-30-PQE |
| contents | Cover -- Copyright -- Table of Contents -- Preface -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. Exploratory Data Analysis -- Elements of Structured Data -- Further Reading -- Rectangular Data -- Data Frames and Indexes -- Nonrectangular Data Structures -- Further Reading -- Estimates of Location -- Mean -- Median and Robust Estimates -- Example: Location Estimates of Population and Murder Rates -- Further Reading -- Estimates of Variability -- Standard Deviation and Related Estimates Estimates Based on Percentiles -- Example: Variability Estimates of State Population -- Further Reading -- Exploring the Data Distribution -- Percentiles and Boxplots -- Frequency Tables and Histograms -- Density Plots and Estimates -- Further Reading -- Exploring Binary and Categorical Data -- Mode -- Expected Value -- Probability -- Further Reading -- Correlation -- Scatterplots -- Further Reading -- Exploring Two or More Variables -- Hexagonal Binning and Contours (Plotting Numeric Versus Numeric Data) -- Two Categorical Variables -- Categorical and Numeric Data Visualizing Multiple Variables -- Further Reading -- Summary -- Chapter 2. Data and Sampling Distributions -- Random Sampling and Sample Bias -- Bias -- Random Selection -- Size Versus Quality: When Does Size Matter? -- Sample Mean Versus Population Mean -- Further Reading -- Selection Bias -- Regression to the Mean -- Further Reading -- Sampling Distribution of a Statistic -- Central Limit Theorem -- Standard Error -- Further Reading -- The Bootstrap -- Resampling Versus Bootstrapping -- Further Reading -- Confidence Intervals -- Further Reading -- Normal Distribution Standard Normal and QQ-Plots -- Long-Tailed Distributions -- Further Reading -- Student's t-Distribution -- Further Reading -- Binomial Distribution -- Further Reading -- Chi-Square Distribution -- Further Reading -- F-Distribution -- Further Reading -- Poisson and Related Distributions -- Poisson Distributions -- Exponential Distribution -- Estimating the Failure Rate -- Weibull Distribution -- Further Reading -- Summary -- Chapter 3. Statistical Experiments and Significance Testing -- A/B Testing -- Why Have a Control Group? -- Why Just A/B? Why Not C, D,...? -- Further Reading Hypothesis Tests -- The Null Hypothesis -- Alternative Hypothesis -- One-Way Versus Two-Way Hypothesis Tests -- Further Reading -- Resampling -- Permutation Test -- Example: Web Stickiness -- Exhaustive and Bootstrap Permutation Tests -- Permutation Tests: The Bottom Line for Data Science -- Further Reading -- Statistical Significance and p-Values -- p-Value -- Alpha -- Type 1 and Type 2 Errors -- Data Science and p-Values -- Further Reading -- t-Tests -- Further Reading -- Multiple Testing -- Further Reading -- Degrees of Freedom -- Further Reading -- ANOVA -- F-Statistic -- Two-Way ANOVA |
| ctrlnum | (OCoLC)1190674899 (DE-599)BVBBV046803637 |
| discipline | Informatik Mathematik |
| edition | Second edition |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV046803637</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20230801</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">200713s2020 xx o|||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781492072911</subfield><subfield code="c">online</subfield><subfield code="9">978-1-492-07291-1</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1190674899</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV046803637</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-1050</subfield><subfield code="a">DE-1043</subfield><subfield code="a">DE-355</subfield><subfield code="a">DE-29</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">SK 850</subfield><subfield code="0">(DE-625)143263:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 250</subfield><subfield code="0">(DE-625)143626:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143650:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 530</subfield><subfield code="0">(DE-625)143679:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Bruce, Peter C.</subfield><subfield code="d">1953-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1104275260</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Practical statistics for data scientists</subfield><subfield code="b">50+ essential concepts using R and Python</subfield><subfield code="c">Peter Bruce, Andrew Bruce, and Peter Gedeck</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">Second edition</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Beijing</subfield><subfield code="b">O'Reilly</subfield><subfield code="c">May 2020</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xvi, 342 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Cover -- Copyright -- Table of Contents -- Preface -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. Exploratory Data Analysis -- Elements of Structured Data -- Further Reading -- Rectangular Data -- Data Frames and Indexes -- Nonrectangular Data Structures -- Further Reading -- Estimates of Location -- Mean -- Median and Robust Estimates -- Example: Location Estimates of Population and Murder Rates -- Further Reading -- Estimates of Variability -- Standard Deviation and Related Estimates</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Estimates Based on Percentiles -- Example: Variability Estimates of State Population -- Further Reading -- Exploring the Data Distribution -- Percentiles and Boxplots -- Frequency Tables and Histograms -- Density Plots and Estimates -- Further Reading -- Exploring Binary and Categorical Data -- Mode -- Expected Value -- Probability -- Further Reading -- Correlation -- Scatterplots -- Further Reading -- Exploring Two or More Variables -- Hexagonal Binning and Contours (Plotting Numeric Versus Numeric Data) -- Two Categorical Variables -- Categorical and Numeric Data</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Visualizing Multiple Variables -- Further Reading -- Summary -- Chapter 2. Data and Sampling Distributions -- Random Sampling and Sample Bias -- Bias -- Random Selection -- Size Versus Quality: When Does Size Matter? -- Sample Mean Versus Population Mean -- Further Reading -- Selection Bias -- Regression to the Mean -- Further Reading -- Sampling Distribution of a Statistic -- Central Limit Theorem -- Standard Error -- Further Reading -- The Bootstrap -- Resampling Versus Bootstrapping -- Further Reading -- Confidence Intervals -- Further Reading -- Normal Distribution</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Standard Normal and QQ-Plots -- Long-Tailed Distributions -- Further Reading -- Student's t-Distribution -- Further Reading -- Binomial Distribution -- Further Reading -- Chi-Square Distribution -- Further Reading -- F-Distribution -- Further Reading -- Poisson and Related Distributions -- Poisson Distributions -- Exponential Distribution -- Estimating the Failure Rate -- Weibull Distribution -- Further Reading -- Summary -- Chapter 3. Statistical Experiments and Significance Testing -- A/B Testing -- Why Have a Control Group? -- Why Just A/B? Why Not C, D,...? -- Further Reading</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Hypothesis Tests -- The Null Hypothesis -- Alternative Hypothesis -- One-Way Versus Two-Way Hypothesis Tests -- Further Reading -- Resampling -- Permutation Test -- Example: Web Stickiness -- Exhaustive and Bootstrap Permutation Tests -- Permutation Tests: The Bottom Line for Data Science -- Further Reading -- Statistical Significance and p-Values -- p-Value -- Alpha -- Type 1 and Type 2 Errors -- Data Science and p-Values -- Further Reading -- t-Tests -- Further Reading -- Multiple Testing -- Further Reading -- Degrees of Freedom -- Further Reading -- ANOVA -- F-Statistic -- Two-Way ANOVA</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical analysis / Statistical methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quantitative research / Statistical methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Big data / Mathematics</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Data Mining</subfield><subfield code="0">(DE-588)4428654-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">R</subfield><subfield code="g">Programm</subfield><subfield code="0">(DE-588)4705956-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Python</subfield><subfield code="g">Programmiersprache</subfield><subfield code="0">(DE-588)4434275-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Datenanalyse</subfield><subfield code="0">(DE-588)4123037-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Data Science</subfield><subfield code="0">(DE-588)1140936166</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Statistik</subfield><subfield code="0">(DE-588)4056995-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Data Science</subfield><subfield code="0">(DE-588)1140936166</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Statistik</subfield><subfield code="0">(DE-588)4056995-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Datenanalyse</subfield><subfield code="0">(DE-588)4123037-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="4"><subfield code="a">Python</subfield><subfield code="g">Programmiersprache</subfield><subfield code="0">(DE-588)4434275-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="5"><subfield code="a">R</subfield><subfield code="g">Programm</subfield><subfield code="0">(DE-588)4705956-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Data Mining</subfield><subfield code="0">(DE-588)4428654-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bruce, Andrew</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)170744183</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gedeck, Peter</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1231483199</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-1-492-07294-2</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032212322</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/th-ab/detail.action?docID=6173908</subfield><subfield code="l">DE-1043</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/th-deggendorf/detail.action?docID=6173908</subfield><subfield code="l">DE-1050</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">FHD01_PQE_Kauf</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/uniregensburg-ebooks/detail.action?docID=6173908</subfield><subfield code="l">DE-355</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">UBR Sammelbestellung 2021</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/erlangen/detail.action?docID=6173908</subfield><subfield code="l">DE-29</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">UER_Einzelkauf</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV046803637 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-30T17:03:44Z |
| institution | BVB |
| isbn | 9781492072911 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032212322 |
| oclc_num | 1190674899 |
| open_access_boolean | |
| owner | DE-1050 DE-1043 DE-355 DE-BY-UBR DE-29 |
| owner_facet | DE-1050 DE-1043 DE-355 DE-BY-UBR DE-29 |
| physical | 1 Online-Ressource (xvi, 342 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE FHD01_PQE_Kauf ZDB-30-PQE UBR Sammelbestellung 2021 ZDB-30-PQE UER_Einzelkauf |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | O'Reilly |
| record_format | marc |
| spellingShingle | Bruce, Peter C. 1953- Bruce, Andrew Gedeck, Peter Practical statistics for data scientists 50+ essential concepts using R and Python Cover -- Copyright -- Table of Contents -- Preface -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. Exploratory Data Analysis -- Elements of Structured Data -- Further Reading -- Rectangular Data -- Data Frames and Indexes -- Nonrectangular Data Structures -- Further Reading -- Estimates of Location -- Mean -- Median and Robust Estimates -- Example: Location Estimates of Population and Murder Rates -- Further Reading -- Estimates of Variability -- Standard Deviation and Related Estimates Estimates Based on Percentiles -- Example: Variability Estimates of State Population -- Further Reading -- Exploring the Data Distribution -- Percentiles and Boxplots -- Frequency Tables and Histograms -- Density Plots and Estimates -- Further Reading -- Exploring Binary and Categorical Data -- Mode -- Expected Value -- Probability -- Further Reading -- Correlation -- Scatterplots -- Further Reading -- Exploring Two or More Variables -- Hexagonal Binning and Contours (Plotting Numeric Versus Numeric Data) -- Two Categorical Variables -- Categorical and Numeric Data Visualizing Multiple Variables -- Further Reading -- Summary -- Chapter 2. Data and Sampling Distributions -- Random Sampling and Sample Bias -- Bias -- Random Selection -- Size Versus Quality: When Does Size Matter? -- Sample Mean Versus Population Mean -- Further Reading -- Selection Bias -- Regression to the Mean -- Further Reading -- Sampling Distribution of a Statistic -- Central Limit Theorem -- Standard Error -- Further Reading -- The Bootstrap -- Resampling Versus Bootstrapping -- Further Reading -- Confidence Intervals -- Further Reading -- Normal Distribution Standard Normal and QQ-Plots -- Long-Tailed Distributions -- Further Reading -- Student's t-Distribution -- Further Reading -- Binomial Distribution -- Further Reading -- Chi-Square Distribution -- Further Reading -- F-Distribution -- Further Reading -- Poisson and Related Distributions -- Poisson Distributions -- Exponential Distribution -- Estimating the Failure Rate -- Weibull Distribution -- Further Reading -- Summary -- Chapter 3. Statistical Experiments and Significance Testing -- A/B Testing -- Why Have a Control Group? -- Why Just A/B? Why Not C, D,...? -- Further Reading Hypothesis Tests -- The Null Hypothesis -- Alternative Hypothesis -- One-Way Versus Two-Way Hypothesis Tests -- Further Reading -- Resampling -- Permutation Test -- Example: Web Stickiness -- Exhaustive and Bootstrap Permutation Tests -- Permutation Tests: The Bottom Line for Data Science -- Further Reading -- Statistical Significance and p-Values -- p-Value -- Alpha -- Type 1 and Type 2 Errors -- Data Science and p-Values -- Further Reading -- t-Tests -- Further Reading -- Multiple Testing -- Further Reading -- Degrees of Freedom -- Further Reading -- ANOVA -- F-Statistic -- Two-Way ANOVA Mathematical analysis / Statistical methods Quantitative research / Statistical methods Big data / Mathematics Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd R Programm (DE-588)4705956-4 gnd Python Programmiersprache (DE-588)4434275-5 gnd Datenanalyse (DE-588)4123037-1 gnd Data Science (DE-588)1140936166 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4802620-7 (DE-588)4428654-5 (DE-588)4705956-4 (DE-588)4434275-5 (DE-588)4123037-1 (DE-588)1140936166 (DE-588)4056995-0 |
| title | Practical statistics for data scientists 50+ essential concepts using R and Python |
| title_auth | Practical statistics for data scientists 50+ essential concepts using R and Python |
| title_exact_search | Practical statistics for data scientists 50+ essential concepts using R and Python |
| title_full | Practical statistics for data scientists 50+ essential concepts using R and Python Peter Bruce, Andrew Bruce, and Peter Gedeck |
| title_fullStr | Practical statistics for data scientists 50+ essential concepts using R and Python Peter Bruce, Andrew Bruce, and Peter Gedeck |
| title_full_unstemmed | Practical statistics for data scientists 50+ essential concepts using R and Python Peter Bruce, Andrew Bruce, and Peter Gedeck |
| title_short | Practical statistics for data scientists |
| title_sort | practical statistics for data scientists 50 essential concepts using r and python |
| title_sub | 50+ essential concepts using R and Python |
| topic | Mathematical analysis / Statistical methods Quantitative research / Statistical methods Big data / Mathematics Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd R Programm (DE-588)4705956-4 gnd Python Programmiersprache (DE-588)4434275-5 gnd Datenanalyse (DE-588)4123037-1 gnd Data Science (DE-588)1140936166 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | Mathematical analysis / Statistical methods Quantitative research / Statistical methods Big data / Mathematics Big Data Data Mining R Programm Python Programmiersprache Datenanalyse Data Science Statistik |
| work_keys_str_mv | AT brucepeterc practicalstatisticsfordatascientists50essentialconceptsusingrandpython AT bruceandrew practicalstatisticsfordatascientists50essentialconceptsusingrandpython AT gedeckpeter practicalstatisticsfordatascientists50essentialconceptsusingrandpython |