Essentials of applied quantitative methods for health services managers
1 / 32

Essentials of Applied Quantitative Methods for Health Services Managers - PowerPoint PPT Presentation

  • Uploaded on

Essentials of Applied Quantitative Methods for Health Services Managers. Class Slides. Chapter 2: Working with Numbers. Learning Objectives: To Be Able to Calculate and Use Descriptive Statistics

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about ' Essentials of Applied Quantitative Methods for Health Services Managers' - nissim-norris

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Chapter 2 working with numbers
Chapter 2: Working with Numbers Services Managers

  • Learning Objectives:

  • To Be Able to Calculate and Use Descriptive Statistics

  • To Be Able to Compare Different Types of Data Using Statistical Inference and Hypothesis Testing

  • To Be Able to Present Data Effectively and Efficiently in Visual Form

Functions of managerial statistics
Functions of Managerial Statistics Services Managers

  • Describe certain data elements

  • Compare two points of data

  • Predict data

Types of data variables
Types of Data Variables Services Managers

  • Nominal – non-overlapping categories, no ranking, and mutually

  • exclusive; e.g., eye color

  • Ordinal – measure categories, but categories have ranks; e.g., satisfaction surveys

  • Interval/Ratio – continuously measured, with equal distance between categories

Descriptive statistics with one variable
Descriptive Statistics with One Variable Services Managers

Insurance type by patient

1 United 8 BC/BS

2 Medicare 9 Medicaid

3 Medicaid 10 Uninsured

4 Medicare 11 Medicare

5 BC/BS 12 Uninsured

6 United 13 United


Measures of central tendency
Measures of Central Tendency Services Managers

Mean – Mathematical Center (Average)

Median – Center of a Distribution of Data, When

Arranged from Lowest to Highest

Mode – Most frequently reported data point

Measures of spread
Measures of Spread Services Managers

Range – Difference between Maximum and Minimum Value

Standard Deviation – Average Distance of a Given

Data Point to the Mean

Working with samples
Working with Samples Services Managers

Samples are Inherently More Variable than Populations

Impossible to Know the “Truth” about Current and/or

Future Population Data – Create an Interval that We Can Say with

Some Level of Confidence Contains the True Population Mean

Formula for Constructing a Confidence Interval:

Mean = +/- 1.96 * Standard Error,

Where Standard Error = Standard Deviation/√n

Working with bivariate data
Working with Bivariate Data Services Managers

Hypothesis Testing

Null Hypothesis: The Hypothesis of No Association or Difference

Alternative Hypothesis: The Converse of the Null Hypothesis; i.e.,

There Is Some Association or Difference

- When the Direction of the Difference Doesn’t Matter 

A Two-Tailed Test. If Direction Does matter, the Test Is

One-Tailed Test

More on hypothesis testing
More on Hypothesis Testing Services Managers

Can Never Be Certain What Relationship Truly IS

Between Two Variables

So, We Use Hypothesis Testing and Statistics to Make Probabilistic

Inferences about Relationships

The normal distribution
The Normal Distribution Services Managers

62” 64” 66” 68” 70” 72” 74”

68-95-99.7 Rule

Comparing continuous data
Comparing Continuous Data Services Managers

Correlation: A Statistical Measure of Association between Two Phenomena – Not a Causal Relationship

r = Correlation Coefficient

R = +1.0 = Perfectly Positive Correlation

R = - 1.0 = Perfectly Negative Correlation

Can Apply Principles of Hypothesis Testing to

Correlation to Assess if There Is a Relationship.

(Use Table of Critical Values (Table 2-4)

The t test
The t-test Services Managers

Compare Differences between Means between Groups


- Paired

- Assuming Equal Variances

- Assuming Unequal Variances

Comparative monthly births
Comparative Monthly Births Services Managers

Sample t test report
Sample t-test Report Services Managers

Comparing categorical data
Comparing Categorical Data Services Managers

  • Often Measured in Rates or Proportions

  • Chi-Square Statistic (X2): Compares Observed Differences

  • in Proportions with What Would Be Expected if Proportions

  • Were Equal

2 x 2 contingency table
2 X 2 Contingency Table Services Managers

Patient satisfaction comparison using chi square
Patient Satisfaction Services ManagersComparison Using Chi Square

The chi square formula
The Chi-Square Formula Services Managers

X2 = Σ((Observed – Expected)2)


Where the Expected Count Is

Row Total * Column Total


Chi square calculations for patient satisfaction data
Chi-Square Calculations for Services ManagersPatient Satisfaction Data

Summary of methods
Summary of Methods Services Managers

Percent of patients overweight or obese by bmi score
Percent of Patients Overweight or Services ManagersObese by BMI Score

A bar chart
A Bar Chart Services Managers

Another bar chart
Another Bar Chart Services Managers

Raw data
Raw Data Services Managers

Pie chart
Pie Chart Services Managers

Raw data1
Raw Data Services Managers

Line graft
Line Graft Services Managers

Raw data2
Raw Data Services Managers

Dual axis graft
Dual Axis Graft Services Managers