3010STATG

Introduction to Statistics for Government 3010STATG (4D)

Introduction to Statistics for Government isn’t just about formulas. Yes, you’ll learn to use quite a few of them, but more importantly, you will learn when and why to use them. You’ll learn how to think as a statistician. At root, statisticians are problem solvers. In this course, you’ll learn to find the midpoint of a data set, discover how the data is distributed, and do calculations that reveal the patterns hidden in data. You’ll also learn to put your statistical knowledge to work to solve real problems at work.

Learning Outcomes

Upon completion of this course, you will be able to do the following:

  • Use the statistical problem-solving process
  • Differentiate between populations and samples
  • Extract a random sample, calculating the viable minimal sample size
  • Select appropriate formulas and use them to gather variables
  • Array data and do initial calculations
  • Use proportions, percentages, and percentage change
  • Run calculations for central tendency, distribution, confidence, and significance
  • Analyze correlations and regressions

Agenda

The course contains the following lessons:

  • Understanding Statistics
  • Using Formulas
  • Calculating Proportion, Percentage, and Percentage Change
  • Gathering and Arraying Data
  • Solving for Different Variables
  • Using Calculators and Software
  • Understanding Populations and Samples
  • Getting a Representative Sample
  • Planning a Sample
  • Selecting Random Samples
  • Random Sampling
  • Using Quantitative Data
  • Using Categorical Data Understanding Central Tendency
  • Calculating Mean
  • Calculating Median
  • Finding and Using Mode
  • Using Central Tendency
  • Understanding the Normal Curve
  • Using Standard Deviation with Populations
  • Using Standard Deviation with Samples
  • Calculating Standard Score
  • Using the Normal Curve Table
  • Developing Confidence Intervals
  • Using Confidence Intervals (Large Sample Percentage)
  • Determining Minimum Sample Size
  • Finding Minimum Sample Size (Categorical Data)
  • Reporting Significance and Confidence
  • Analyzing Correlation
  • Calculating the Correlation Coefficient (r)
  • Understanding Linear Equations
  • Calculating Regression
  • Finding Confidence Intervals for Regression
  • Understanding the Statistical Problem-­‐Solving Process
  • Creating a Causal Model
  • Developing Hypotheses
  • Interpreting and Recommending
  • Graphing Results
  • Avoiding Distortions