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# Confidence Intervals and Hypothesis Testing resources

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### 02. Video Tutorials (4)

Compute z-scores for variables in SPSS
How to use SPSS to compute z-scores for a variable. Choose one of two available methods. This resource from the "SPSS Tutorial Series" is contributed to the statstutor Community project by Christine Pereira, Brunel University and reviewed by Tim Sparks, Coventry University. It was developed with sigma resource development funding.
Confidence Intervals and Error Bars in SPSS
A short video tutorial to demonstrate how to calculate confidence intervals and error bars using SPSS. This resource has been made available under a Creative Commons licence by Kristian Evans, Swansea University.
Interpret SPSS output for a paired t-test
How to interpret SPSS output for a paired t-test. Includes the p-value and confidence intervals for the mean difference. This resource from the "SPSS Tutorial Series" is contributed to the statstutor Community project by Christine Pereira, Brunel University and reviewed by Jonathan Gillard, Cardiff University. It was developed with sigma resource development funding.
Interpret SPSS output for an independent t-test
How to interpret SPSS output for an independent t-test (also known as a two-sample t-test). Includes Levene's test for homogeneity of variance, p-value and confidence intervals for the mean difference. This resource from the "SPSS Tutorial Series" is contributed to the statstutor Community project by Christine Pereira, Brunel University and reviewed by Jonathan Gillard, Cardiff University. It was developed with sigma resource development funding.

### 04. Tests and Quizzes (4)

Business Statistics 4 - Numbas
5 questions. 1. Finding the confidence interval at either 90%, 95% or 99% for the mean given the mean and standard deviation of a sample. The population variance is not given and so the t test has to be used. Various scenarios are included. 2. Finding the confidence interval at either 90%, 95% or 99% for the mean given the mean of a sample. The population variance is given and so the z values are used. Various scenarios are included. 3. Provided with information on a sample with sample mean and standard deviation, but no information on the population variance, use the t test to either accept or reject a given null hypothesis. 4. Provided with information on a sample with sample mean and known population variance, use the z test to either accept or reject a given null hypothesis. 5. Given two sets of data, sample mean and sample standard deviation, on performance on the same task, make a decision as to whether or not the mean times differ. Population variance not given, so the t test has to be used in conjunction with the pooled sample standard deviation. Link to use of t tables and p-values in Show steps. Numbas resources have been made available under a Creative Commons licence by the School of Mathematics & Statistics at Newcastle University.
Business statistics 4 - Numbas
5 questions on confidence intervals and hypothesis testing. Population variance given, z-test. Not given, t-test. Numbas resources have been made available under a Creative Commons licence by Bill Foster and Christain Perfect, School of Mathematics & Statistics at Newcastle University.
Hypothesis testing with the Student t-distribution - Numbas
Three questions on using the Student $t$ distribution to perform hypothesis tests.
Parametric hypothesis testing for psychology - Numbas
Three questions on parametric hypothesis testing and confidence intervals, aimed at psychology students. Numbas resources have been made available under a Creative Commons licence by Bill Foster and Christain Perfect, School of Mathematics & Statistics at Newcastle University.

### 07. Community Project (1)

Statistical hypothesis testing SOURCE
A Quick Reference worksheet on an introduction to statistical hypothesis testing. This resource has been contributed to the statstutor Community Project by Mollie Gilchrist and Peter Samuels, Birmingham City University under a Creative Commons licence CC-BY-SA and reviewed by Ellen Marshall, University of Sheffield. The zip file contains the source file and the associated statstutor metadata spreadsheet.

### 08. Staff Resources (4)

Data for SPSS Workbook for New Statistics Tutors (Excel file)
Data sets for the self-study training resource for new statistics tutors entitled "SPSS Workbook for New Statistics Tutors". These were developed by Ellen Marshall (University of Sheffield) and reviewed by Jean Russell (University of Sheffield).
Introductory Statistics and Hypothesis Testing (PowerPoint Workshop)
These slides are aimed to be used in a workshop to train mathematics (or new statistics) tutors who need to provide statistics support. They cover key topics including hypothesis testing and choosing the right test. These slides were developed and contributed to the statstutor Community Project by Alun Owen (University of Worcester) and Ellen Marshall (University of Sheffield) and reviewed by Ruth Fairclough (University of Wolverhampton).
Solutions for SPSS Workbook for New Statistics Tutors
Solutions to the self-study training resource for new statistics tutors entitled "SPSS Workbook for New Statistics Tutors". These were developed and contributed to the statstutor Community Project by Ellen Marshall (University of Sheffield) and reviewed by Jean Russell (University of Sheffield).
SPSS Workbook for New Statistics Tutors
This is a paper-based scenario aimed to be used as part of the tutor training workshop using the resource entitled "Introductory Statistics and Hypothesis Testing". This was developed and contributed to the statstutor Community Project by Alun Owen (University of Worcester) and Ellen Marshall (University of Sheffield) and reviewed by Jean Russell (University of Sheffield).

### 11. Quick reference worksheet (1)

Statistical hypothesis testing
A Quick Reference worksheet on an introduction to statistical hypothesis testing. This resource has been contributed to the statstutor Community Project by Mollie Gilchrist and Peter Samuels, Birmingham City University and reviewed by Ellen Marshall, University of Sheffield.

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