LEADER 01109nam a2200289 i 4500 001 991001751939707536 008 030730s1997 be d b 001 0 lat 020 $a2503047017 035 $ab12192004-39ule_inst 040 $aBiblioteca Interfacoltà$bita 082 04$a223.9077 130 0$aBibbia.$nVecchio Testamento.$nCantico dei cantici $955323 245 00$aIn Canticum canticorum /$cedidit Mary Dove 260 $aTurnholti :$bTypographi Brepols,$c1997 300 $a454 p., [1] c. di tav. :$bill. ;$c26 cm 440 0$aGlossa ordinaria ;$vpars 22 440 0$aCorpus Christianorum. Continuatio Mediaevalis ;$v170 500 $aVersione inglese a fronte 504 $aInclude bibliografia e indici 630 04$aBibbia.$nVecchio Testamento.$nCantico dei cantici$xGlosse 700 1 $aDove, Mary 907 $a.b12192004$b02-04-14$c30-07-03 912 $a991001751939707536 945 $aLE002 Patr. CCCM 170$g1$i2002000237859$lle002$o-$pE0.00$q-$rn$so $t0$u0$v0$w0$x0$y.i12556816$z30-07-03 996 $aBibbia$955323 997 $aUNISALENTO 998 $ale002$b30-07-03$cm$da $e-$flat$gbe $h0$i0 LEADER 06051nam 22005533 450 001 9911007182203321 005 20231215080328.0 010 $a9781683928782 010 $a1683928784 010 $a9781683928799 010 $a1683928792 024 7 $a10.1515/9781683928799 035 $a(MiAaPQ)EBC31015589 035 $a(Au-PeEL)EBL31015589 035 $a(DE-B1597)658517 035 $a(DE-B1597)9781683928799 035 $a(CKB)29354973000041 035 $a(FR-PaCSA)88949074 035 $a(FRCYB88949074)88949074 035 $a(Perlego)4310543 035 $a(EXLCZ)9929354973000041 100 $a20231215d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistics Using Python 205 $a1st ed. 210 1$aBloomfield :$cMercury Learning & Information,$d2023. 210 4$d©2023. 215 $a1 online resource (273 pages) 311 08$a9781683928805 311 08$a1683928806 327 $aFront Cover -- Half-Title Page -- LICENSE, DISCLAIMER OF LIABILITY, AND LIMITED WARRANTY -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- CHAPTER 1: Working with Data -- What is Data Literacy? -- Exploratory Data Analysis (EDA) -- Dealing with Data: What Can Go Wrong? -- An Explanation of Data Types -- Working with Data Types -- What is Drift? -- Discrete Data Versus Continuous Data -- Binning Data Values -- Correlation -- Working with Synthetic Data -- Summary -- CHAPTER 2: Introduction to Probability -- What is Set Theory? -- Open, Closed, Compact, and Convex Sets (Optional) -- Concepts in Probability -- Set Theory and Probability -- Coin Tossing Probabilities -- Dice Tossing Probabilities -- Card Drawing Probabilities -- Container-Based Probabilities -- Children-Related Probabilities -- Summary -- CHAPTER 3: Introduction to Statistics -- Introduction to Statistics -- Basic Concepts in Statistics -- The Variance and Standard Deviation -- The Moments of a Function (Optional) -- Random Variables -- Multiple Random Variables -- Sampling Techniques for a Population -- What is Bias? -- Two Important Results in Probability -- Summary -- CHAPTER 4: Metrics in Statistics -- The Confusion Matrix -- The ROC Curve and AUC Curve -- The sklearn.metrics Module (Optional) -- Statistical Metrics for Categorical Data -- Metrics for Continuous Data -- MAE, MSE, and RMSE -- Approximating Linear Data with np.linspace() -- Summary -- CHAPTER 5: Probability Distributions -- PDF, CDF, and PMF -- Two Types of Probability Distributions -- Discrete Probability Distributions -- Continuous Probability Distributions -- Advanced Probability Functions -- Non-Gaussian Distributions -- The Best-Fitting Distribution for Data -- Summary -- CHAPTER 6: Hypothesis Testing -- What is Hypothesis Testing? -- Components of Hypothesis Testing -- Test Statistics. 327 $aWorking with p-values -- Working with Alpha Values -- Point Estimation, Confidence Level, and Confidence Intervals -- What is A/B Testing? -- The Lifespan of an A/B Test -- Maximum Likelihood Estimation (MLE) -- Summary -- Appendix A: Introduction to Python -- Tools for Python -- Python Installation -- Setting the PATH Environment Variable (Windows Only) -- Launching Python on Your Machine -- Identifiers -- Lines, Indentation, and Multi-Line Statements -- Quotation Marks and Comments -- Saving Your Code in a Module -- Some Standard Modules -- The help() and dir() Functions -- Compile Time and Runtime Code Checking -- Simple Data Types -- Working with Numbers -- Working with Fractions -- Unicode and UTF-8 -- Working with Strings -- Slicing and Splicing Strings -- Search and Replace a String in Other Strings -- Remove Leading and Trailing Characters -- Printing Text without New Line Characters -- Text Alignment -- Working with Dates -- Exception Handling -- Handling User Input -- Python and Emojis (Optional) -- Command-Line Arguments -- Summary -- Appendix B: Introduction to Pandas -- What is Pandas? -- A Pandas Data Frame with a NumPy Example -- Describing a Pandas Data Frame -- Boolean Data Frames -- Data Frames and Random Numbers -- Reading CSV Files in Pandas -- The loc() and iloc() Methods -- Converting Categorical Data to Numeric Data -- Matching and Splitting Strings -- Converting Strings to Dates -- Working with Date Ranges -- Detecting Missing Dates -- Interpolating Missing Dates -- Other Operations with Dates -- Merging and Splitting Columns in Pandas -- Reading HTML Web Pages -- Saving a Pandas Data Frame as an HTML Web Page -- Summary -- Index. 330 $aThis book is designed to offer a fast-paced yet thorough introduction to essential statistical concepts using Python code samples, and aims to assist data scientists in their daily endeavors. The ability to extract meaningful insights from data requires a deep understanding of statistics. The book ensures that each topic is introduced with clarity, followed by executable Python code samples that can be modified and applied according to individual needs. Topics include working with data and exploratory analysis, the basics of probability, descriptive and inferential statistics and their applications, metrics for data analysis, probability distributions, hypothesis testing, and more. Appendices on Python and Pandas have been included. From foundational Python concepts to the intricacies of statistics, this book serves as a comprehensive resource for both beginners and seasoned professionals. 606 $aPython (Computer program language)$xStatistical methods 606 $aMATHEMATICS / Probability & Statistics / General$2bisacsh 615 0$aPython (Computer program language)$xStatistical methods. 615 7$aMATHEMATICS / Probability & Statistics / General. 700 $aCampesato$b Oswald$01594522 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911007182203321 996 $aStatistics Using Python$94392769 997 $aUNINA