SPSS for healthcare and life science statistics
4.1 (29 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
121 students enrolled

SPSS for healthcare and life science statistics

Learn to conduct the most common statistical tests using SPSS
4.1 (29 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
121 students enrolled
Created by Juan Klopper
Last updated 4/2017
English [Auto-generated]
Current price: $11.99 Original price: $24.99 Discount: 52% off
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This course includes
  • 1.5 hours on-demand video
  • 3 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Be familiar with the SPSS user interface
  • Be able to import research data

  • Conduct descriptive statistical analysis

  • Create figures, plots, and graphs from data
  • Compare numerical data point values between categorical groups
  • Conduct tests for categorical variables
  • Students who enroll in this course should have access to a computer that runs a copy of IBM's SPSS Statistics software. Only a very basic understanding of statistics is required.

If you want to analyze your own data or need to work in a research team that uses IBM's SPSS software, then this course is for you.

From the import of data, through descriptive statistics, data visualization, correlation, the comparison of means, and the analysis of categorical variables, this course will leave you familiar with the user interface and able to conduct all of the most common statistical tests.

Who this course is for:
  • Professionals and students in healthcare and life science.
Course content
Expand all 31 lectures 01:39:33
+ A big hello to all students taking this course
1 lecture 01:29

A warm welcome from me to this course on using SPSS for healthcare and life science statistics.  I hope to empower you to do your own statistical analysis or be comfortable working in a team that uses SPSS, still the most widely used statistical software package for healthcare in the world.

Preview 01:29
+ Descriptive statistics
3 lectures 12:27

In this section we will take a look at importing data and we will conduct a variety of descriptive statistical analysis.

Preview 00:31

In the analysis of data, the first step is to calculate measures of central tendency and dispersion.  The mean, median, and mode are common point estimates (measures of central tendency).  Standard deviation, variance, range, and quantiles are common measures of dispersion.

These values summarize our data and makes it easier to interpret.

01 Instruction to descriptive statistics

In this section we calculate common measures of central tendency and dispersion.  These include, mean, median, and standard deviation among others.

02 Calculating common descriptive statistics
+ Graphs
11 lectures 28:54

This section is all about learning the details of your dataset through visualization.

Preview 00:39

The visualization of data is another important first step in analyzing data.  As humans, we get a better understanding of our data when it is visualized.  It is indeed much better than staring at columns of numbers.

SPSS can generate almost all of the graphs, plots, and figures that you will ever need.  While the default settings are not the most pleasing, rest assured that you can change all the aspect of your graphs.

01 Introduction to graphs

In this video you will see the dataset that will be used in this course.  It should easily generalize to your unique research area and contains a good mix of nominal, ordinal, and numerical variables.

02 The data

Histograms are frequency charts.  It divides the range of data points values for a numerical variable into equally-sized bins and counts the occurrence of values in each of these bins.

Preview 06:32

If you want to fit a histogram of a dependent variable for more than one independent variable, a stacked histogram is the way to go.

04 Stacked histogram

Another way of comparing the histograms for a variable between two groups, is the population pyramid.  It creates two horizontal histograms.

05 Population pyramid

A bar chart can be used to count the instances of unique data point values for a categorical variable.

06 Bar chart

Box-and-whisker charts are the most commonly used figures in the healthcare literature.  They convey useful information.

07 Box-and-whisker chart

A scatter chart plots pairs of values.  It is the preferred method at investigation the correlation between two variables.

08 Scatter plot

SPSS can create scatter plots for a pair of variables for more than one independent group.

09 Scatter plot for more than one group

Instead of pie charts, I recommend frequency tables.  In this video I show you how to create them.

10 Frequency table
+ Correlation
4 lectures 15:53

Are two numerical variables from each research subject somehow connected?  Does a change in one lead to a change in the other?  This section looks at correlation.

Introduction to this section on correlation

I quick refresher on correlation.

01 Introduction to correlation

The main assumptions for the use of Pearson's coefficient correlation include:

  1. A linear relationship between the variables
  2. A normal distribution of the variable in the underlying population
  3. No statistical outliers
02 Assumptions for correlation

In this video we look at how to conduct a correlation test when the assumptions in the previous video are met.

Preview 03:15
+ Comparing means with t-tests and analysis of variance
8 lectures 31:58

The meat and potatoes of the course as my grandmother would have said.  The various t-tests, including Student's t-test and analysis of variance are the most common tests that you will conduct and see in the literature.

Introduction to this section on comparing means between groups

In this video, we discuss the comparison of mean values between two or more groups.

01 omparing the means of a numerical variable between groups

Student's t-test is one of the most common statistical tests in the literature.  The t-tests compares the mean values for a numerical variable between two groups.

A variety of assumptions must be met before we can use these tests.

02 The independent sample t-test

In this video we take a look at how to test for the assumptions for the use of t-tests and how to compare them.

03 The independent samples t-test in SPSS

The paired samples t-test compares the means for the same variable, measured twice in the sample sample subject.

04 The paired samples t-test

In this video we take a look at how to calculate a new variable that measures the difference between each pair of data point values.  We then look at the assumptions for this test before actually conducting it.

05 The paired samples t-test in SPSS

Fisher's test allows us to calculate the difference in means between more than two groups.  It has similar assumptions at the t-tests.

06 Comparing the means of more than two groups

In this video we use analysis of variance two compare the means of more than two groups.

07 Comparing the means of more than two groups in SPSS
+ Tests for categorical variables
3 lectures 08:28

This section leaves numerical variables behind and looks at the common tests for categorical variables.

Preview 00:28

Now that we have seen the most common tests for numerical variables, let's take a look at the tests for categorical variables.

01 Introduction to tests for categorical variables

Let's have a look at conducting the chi-squared tests for independence and Fisher's exact test in SPSS.

02 Conducting tests for categorical variables in SPSS
+ The end
1 lecture 00:24

Thanks!  I really enjoyed putting this course together.  Not only is it available to everyone in the world, but it is also for official use in my own Department.

The end