Statistics, Data Analysis, Decision Analysis, Quantitative Methods classes and training in Sacramento, California

Theoretical statistics training gives you the opportunity to learn statistics and its applications. By learning Statistics you have better job opportunities, you can make better decisions for your business and your personal life and you can think of continuing education in any field with confidence as most of the subjects in College or Universities require statistics in  a way. This training helps those who want to be successful in careers such as analysts, computer programmers, actuaries, researchers, human resource analysts, decision analysis, planners and educators and many other careers.

You can step up in your career by learning Statistics, particularly if you learn a software to analyze data.
TOPICS on Basics Training
Basic Statistics and Quantitative methods using Microsoft Excel is vital to develop analytical skills. Better decisions are outcome of such skills and it‘s for both researchers and business managers.
What you will learn:
1. Qualitative and Quantitative data collection,
2. Data entry, data cleaning, analysis and decision making
3. From problem statement to research questions and frameworks (models) and/or hypothesis testing
4. Differentiate and use different statistical tests to solve problems
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
- Inferential Statistics
- Type of variables and measurement levels
- Sample and Population
- Entering and Cleaning Data
Descriptive Statistics
- Frequency tables, Pie chart, Bar chart, Histogram
- Mean, Mode, Median
- Skewness, Standard Deviation, Variance
Hypothesis Testing for differences
- t-tests ( 1-sample test , 2-smaple test and paired t-test)
- Analysis of Variance (ANOVA)
Hypothesis Testing for Relations
- Graphing scatter diagram
- Correlations and Regression Analysis (Simple linear regression)
- graphing results
Decision Analysis
Interpretation, sensitivity analysis, writing report, conclusion and more.
- Review of Descriptive Statistics
Scale of Measurement
- Tests & Assumptions
- Multivariate Statistics
Why Study Multivariate Statistics
Univariate and Bivariate Statistics
- Reliability
- Data Appropriate for Multivariate Statistics
Correlation and Partial Correlation
Hypothesis Testing
- Multiple Regression  (1)
General Purpose and Description
Theoretical Issues: Assumptions
Data Analysis and Interpretation
- Multiple Regression (2)
Factor Analysis (Exp. & Com.)
Basics of Logistic Regression (LR)
Interpretation of LR
- Statistical technics to compare groups (1)
Non Parametric statistics
T test
One way ANOVA
- Statistical technics to compare groups (2)
Two ways ANOVA
MANOVA
Analysis of Covariance (ANCOVA)
Introduction to SEM (Structural Equation Modelling)
- Time Series & Forecasting