text: Basics of Statistics Using MS Excel (Microsoft Excel)
  
  Basic Statistics and Quantitative methods using Microsoft Excel is vital to develop analytical skills. Better decisions are outcome of such skills and itâ€˜s for both researchers and business managers.
  
  What you will learn:
  1. Quantitative data collection,
  2. Data entry, data cleaning, analysis and decision making using Microsoft Excel
  3. From problem statement to research questions and frameworks (models) and/or hypothesis testing using Microsoft Excel
  4. Differentiate and use different statistical tests to solve problems using Microsoft Excel
  5. Writing Interpretation and report.
  
  The focus of this class is on using Microsoft Excel to solve statistics problems.
  
  Subjects that we cover:
  - Basic Statistics (Microsoft Excel)
  - Inferential Statistics (Microsoft Excel)
  - Type of variables and measurement levels (Microsoft Excel)
  - Sample and Population (Microsoft Excel)
  - Data with Microsoft Excel
  - Entering and Cleaning Data (Microsoft Excel)
  Descriptive Statistics  (Microsoft Excel)
  - Frequency tables, Pie chart, Bar chart, Histogram (Microsoft Excel)
  - Mean, Mode, Median (Microsoft Excel)
  - Skewness, Standard Deviation, Variance (Microsoft Excel)
  Hypothesis Testing for differences (Microsoft Excel)
  - t-tests ( 1-sample test , 2-smaple test and paired t-test) (Microsoft Excel)
  - Analysis of Variance (ANOVA) (Microsoft Excel)
  Hypothesis Testing for Relations (Microsoft Excel)
  - Graphing scatter diagram (Microsoft Excel)
  - Correlations and Regression Analysis (Simple linear regression) (Microsoft Excel)
  
  Decision Analysis using the results from Microsoft Excel
  Interpretation, sensitivity analysis, writing report, conclusion and more. (Microsoft Excel)
  
  - Review of Descriptive Statistics
  Scale of Measurement
  - Tests & Assumptions
  - Multivariate Statistics (Microsoft Excel)
  Why Study Multivariate Statistics
  Univariate and Bivariate Statistics (Microsoft Excel)
  - Reliability (Microsoft Excel)
  - Data Appropriate for Multivariate Statistics
  Correlation and Partial Correlation (Microsoft Excel)
  Hypothesis Testing (Microsoft Excel)
  - Multiple Regression  (1) (Microsoft Excel)
  General Purpose and Description
  Theoretical Issues: Assumptions
  Data Analysis and Interpretation
  - Multiple Regression (2) (Microsoft Excel)
  Factor Analysis (Exp. & Com.)
  Basics of Logistic Regression (LR)
  Interpretation of LR
  - Statistical technics to compare groups (1)
  Non Parametric statistics (Microsoft Excel)
  T test
  One way ANOVA (Microsoft Excel)
  - Statistical technics to compare groups (2)
  Two ways ANOVA (Microsoft Excel)
  MANOVA
  Analysis of Covariance (ANCOVA)
  Introduction to SEM (Structural Equation Modelling)
explanation: The document is a course outline for a class on basic statistics and quantitative methods using Microsoft Excel. It covers various topics such as data collection, data entry, data cleaning, descriptive and inferential statistics, hypothesis testing, and decision analysis. The outline lists the subjects and techniques that will be covered, but it does not contain any specific math questions or answers.
distilabel_metadata.content: Evaluate the user given text extract and determine if it contains a math question and optionally and answer to this question.
  
  Output rules:
  
  1. Briefly describe the document and mention if it contains a question or a question and answer.
  2. Finalize the output with: Label: no-question,question,question-and-answer,multiple-question,multiple-question-and-answer
distilabel_metadata.role: system
distilabel_metadata.content: Basics of Statistics Using MS Excel (Microsoft Excel)
  
  Basic Statistics and Quantitative methods using Microsoft Excel is vital to develop analytical skills. Better decisions are outcome of such skills and itâ€˜s for both researchers and business managers.
  
  What you will learn:
  1. Quantitative data collection,
  2. Data entry, data cleaning, analysis and decision making using Microsoft Excel
  3. From problem statement to research questions and frameworks (models) and/or hypothesis testing using Microsoft Excel
  4. Differentiate and use different statistical tests to solve problems using Microsoft Excel
  5. Writing Interpretation and report.
  
  The focus of this class is on using Microsoft Excel to solve statistics problems.
  
  Subjects that we cover:
  - Basic Statistics (Microsoft Excel)
  - Inferential Statistics (Microsoft Excel)
  - Type of variables and measurement levels (Microsoft Excel)
  - Sample and Population (Microsoft Excel)
  - Data with Microsoft Excel
  - Entering and Cleaning Data (Microsoft Excel)
  Descriptive Statistics  (Microsoft Excel)
  - Frequency tables, Pie chart, Bar chart, Histogram (Microsoft Excel)
  - Mean, Mode, Median (Microsoft Excel)
  - Skewness, Standard Deviation, Variance (Microsoft Excel)
  Hypothesis Testing for differences (Microsoft Excel)
  - t-tests ( 1-sample test , 2-smaple test and paired t-test) (Microsoft Excel)
  - Analysis of Variance (ANOVA) (Microsoft Excel)
  Hypothesis Testing for Relations (Microsoft Excel)
  - Graphing scatter diagram (Microsoft Excel)
  - Correlations and Regression Analysis (Simple linear regression) (Microsoft Excel)
  
  Decision Analysis using the results from Microsoft Excel
  Interpretation, sensitivity analysis, writing report, conclusion and more. (Microsoft Excel)
  
  - Review of Descriptive Statistics
  Scale of Measurement
  - Tests & Assumptions
  - Multivariate Statistics (Microsoft Excel)
  Why Study Multivariate Statistics
  Univariate and Bivariate Statistics (Microsoft Excel)
  - Reliability (Microsoft Excel)
  - Data Appropriate for Multivariate Statistics
  Correlation and Partial Correlation (Microsoft Excel)
  Hypothesis Testing (Microsoft Excel)
  - Multiple Regression  (1) (Microsoft Excel)
  General Purpose and Description
  Theoretical Issues: Assumptions
  Data Analysis and Interpretation
  - Multiple Regression (2) (Microsoft Excel)
  Factor Analysis (Exp. & Com.)
  Basics of Logistic Regression (LR)
  Interpretation of LR
  - Statistical technics to compare groups (1)
  Non Parametric statistics (Microsoft Excel)
  T test
  One way ANOVA (Microsoft Excel)
  - Statistical technics to compare groups (2)
  Two ways ANOVA (Microsoft Excel)
  MANOVA
  Analysis of Covariance (ANCOVA)
  Introduction to SEM (Structural Equation Modelling)
distilabel_metadata.role: user
distilabel_metadata.raw_output_q_a_detector_0: The document is a course outline for a class on basic statistics and quantitative methods using Microsoft Excel. It covers various topics such as data collection, data entry, data cleaning, descriptive and inferential statistics, hypothesis testing, and decision analysis. The outline lists the subjects and techniques that will be covered, but it does not contain any specific math questions or answers.
  
  Label: no-question