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Meer over Van Haren Learning SolutionsData Analysis Foundation Courseware
E-book Pdf met watermerkbeveiliging Engels 2024 1e druk 9789401810715Samenvatting
This Data Analysis Foundation Courseware enable a Data Analysis Foundation course, providing a comprehensive introduction to data concepts and the essence of data analysis, subsequently delving into the fundamental principles of Data Analysis, such as statistics and probability. Moreover, this course concentrates on extensively used data analysis techniques like regression and a step-by-step guide to executing them.
Data Analysis refers to the systematic application of statistical and mathematical techniques to gain insights, explore, and scrutinize data in order to identify patterns and draw meaningful conclusions that assist businesses in making informed decisions based on data. This process typically encompasses various stages, including data collection, exploration, cleansing, pre-processing, and data organization. Frequently, data analysis is an ongoing, iterative procedure wherein data is continuously collected and analyzed simultaneously. There are two primary approaches to data analysis.
Quantitative techniques involve working with numerical data and employ statistical measures, percentages, and calculations. These methods utilize algorithms, mathematical analysis tools, and software to manipulate data and reveal concealed business value. For instance, quantitative data analysis is employed to evaluate market data, aiding a company in determining an appropriate price for a new product.
Qualitative data analysis entails working with non-numerical data, specifically categorical variables. Qualitative data analysis is also applicable in various business processes, including identifying themes and patterns and addressing research inquiries, aiming to enhance a product.
Specificaties
Lezersrecensies
Inhoudsopgave
Agenda 10
Section 1: Introduction to Data (4) 14
Data in practical applications (7) 16
Formats and sources of data (13) 19
The 7 Vs of big data (17) 21
Structured, semi-structured, and unstructured data (25) 25
Data Processing Techniques (30) 27
Section 2: Fundamentals of Data Analysis (34) 29
Importance of Data Analysis (37) 31
Application of data analysis (39) 32
The process of analyzing data (45) 35
Numerical data (51) 38
Categorical data (54) 39
Section 3: Descriptive Data & Statistics (60) 42
Descriptive statistics in data analysis (64) 44
Frequency (72) 48
Measures of central tendency (77) 51
Measures of dispersion (85) 55
Data skewness and kurtosis (98) 61
Outliers (105) 64
Missing values (108) 66
Section 4: Probability (112) 68
Probability overview (115) 69
Axioms of probability (121) 72
Conditional probability and Bayes’ theorem (129) 76
Section 5: Probability Distributions (137) 80
Discrete probability distributions (140) 82
Continuous probability distributions (150) 87
Performing distributions in Excel (157) 90
Importance of data distribution for data analysis (159) 91
Section 6: Executing Data Analysis (161) 92
Covariance and correlation (164) 94
Univariate, bivariate, and multivariate analysis (174) 99
Linear regression (178) 101
Simple linear regression (184) 104
Multiple linear regression (195) 109
Knowledge Check Answers (198) 111
Sample exam 113
Syllabus 130
Rubrieken
- advisering
- algemeen management
- coaching en trainen
- communicatie en media
- economie
- financieel management
- inkoop en logistiek
- internet en social media
- it-management / ict
- juridisch
- leiderschap
- marketing
- mens en maatschappij
- non-profit
- ondernemen
- organisatiekunde
- personal finance
- personeelsmanagement
- persoonlijke effectiviteit
- projectmanagement
- psychologie
- reclame en verkoop
- strategisch management
- verandermanagement
- werk en loopbaan