Hypothesis is a term that is often used in many ways (for example, sometimes it means that you have a feeling that something is true), but it has a p
Hypothesis is a term that is often used in many ways (for example, sometimes it means that you have a feeling that something is true), but it has a precise meaning in statistics. Hypotheses are the likely answers to our testable research questions. Hypotheses are derived from prior knowledge and questions that arise from previously conducted research – they represent what people still need to learn about a particular area (Wagner III & Gillespie, 2019).
For example, you know that water is required to sustain life, and you recently discovered snow on Mars. Now, astronomers are exploring the research question, “Can Mars sustain human life?” Their hypothesis could be, “If there is water on Mars, then humans will be able to survive.” Notice that this is a testable statement! Through observation or experiments, you can determine whether this hypothesis is true or false. Notice, too, that the hypothesis indicates the relation between the independent variable (available water) and the dependent variable (sustaining human life). This week, you will learn to write strong hypotheses for statistical analyses.
You will also learn about statistical errors. Since it is not possible to be completely confident in the results of a study, researchers accept – but try to reduce – the probability of error in their conclusions. When testing a hypothesis, your first step will be to name the null hypothesis, which is typically the default state. This is done within this nation’s legal system all the time – the default state, or the null hypothesis, is that any accused person is not guilty. Then, people test that hypothesis through the process of an investigation and a trial. The result of this test may be that people reject the null hypothesis – or replace the default state (‘this person is not guilty’) with something else (‘this person is guilty’). If the result of this test corresponds with reality, then individuals made the correct decision to reject the null hypothesis. However, if the result of the test does not correspond with reality, then an error has occurred. There are two types of error that you will explore this week: Type I error, also referred to as “false positive”, when you reject the null hypothesis, but it is true (in this example, you claim that a person is guilty, but in reality, the person is not) and Type II error, also known as “false negative”, when you keep the null hypothesis though it is false (you find the accused person innocent, but in reality, that person did commit the crime). You can see that each type of error has consequences; you will be introduced to guidelines for statistical testing that can help you limit the errors in your analyses.
This week, you will also explore inferential statistics like T test, which will help in hypothesis testing and arriving at conclusions about the hypothesis. Inferential statistics use a random sample from a population to describe a population, thus being able to make inferences about the population as a whole. A T test is used to compare two groups of means to determine if there is a statistically significant difference between the groups. The basic premise behind the T test statistic is to compare distributions based on the difference between means. In the simplest terms, the logic is to calculate the difference between means (Wagner III & Gillespie, 2019).
You will learn that there are different types of T tests like One sample T test, Paired Sample T test, and Independent sample T test that can be used depending on the research design. Importance is placed on calculating these tests by using statistical software, as well as analyzing and interpreting their results. In addition to manipulating computations, the conceptual basis of each test will be explored.
References
Wagner III, W., & Gillespie, B. (2019). Using and interpreting statistics in the social, behavioral, and health sciences. Thousand Oaks, CA: SAGE.
Weekly Resources and Assignments
Review the resources from the Course Resources link, located in the top navigation bar, to prepare for this week’s assignments. The resources may include textbook reading assignments, journal articles, websites, links to tools or software, videos, handouts, rubrics, etc.
0 %0 of 1 topics completeShow data table for This chart displays the number of completed topics versus the total number of topics within module Week 6..
List of Topics and Sub-Modules for Week 6
Instructions
Download the assignment template and data file from this week’s resources and review the steps for this assignment. Once you have reviewed the steps, complete the problems and questions as presented. Show your work using your statistical program output. You may show manual/hand calculations only if the SPSS program cannot be accessed. There are two deliverables you must submit this week:
- SPSS output file or manual calculations: Submit the SPSS output file in PDF form, or you can scan your work and submit it as a low-resolution graphic.
- Word document: Submit a Word file answering the questions asked in the assignment. Describe the results in APA style incorporating relevant tables and figures formatted in APA style.
Length: SPSS output or manual calculations and 1 to 2-page Word document
The completed assignment should address all of the assignment requirements, exhibit evidence of concept knowledge, and demonstrate thoughtful consideration of the content presented in the course. The writing should integrate scholarly resources, reflect academic expectations and current APA standards, and adhere to Northcentral University's Academic Integrity Policy.
- Week 6 – Assignment: Complete a T testAssignment Due June 12 at 11:59 PMDownload the assignment template and data file from this week’s resources and review the steps for this assignment. Once you have reviewed the steps, complete the problems and questions as presented. Show your work using your statistical program output. You may show manual/hand calculations only if the SPSS program cannot be accessed. There are two deliverables you must submit this week:
- SPSS output file or manual calculations: Submit the SPSS output file in PDF form, or you can scan your work and submit it as a low-resolution graphic.
- Word document: Submit a Word file answering the questions asked in the assignment. Describe the results in APA style incorporating relevant tables and figures formatted in APA style.
- Length: SPSS output or manual calculations and 1 to 2-page Word document
The completed assignment should address all of the assignment requirements, exhibit evidence of concept knowledge, and demonstrate thoughtful consideration of the content presented in the course. The writing should integrate scholarly resources, reflect academic expectations and current APA standards, and adhere to Northcentral University's Academic Integrity Policy.
PSY-7104 Statistics I
Week 6 Assignment
Elaine is interested in determining if men are more satisfied in their jobs than women in the healthcare industry. She administers a job satisfaction questionnaire to 20 men and 20 women working in hospital administration. Her grouping variable is gender and dependent variable is job satisfaction. The job satisfaction scale consists of 8 items measured using a 5-point rating scale. A higher score on this scale would indicate high job satisfaction. The maximum score that can be obtained on the scale is 40. We can assume that job satisfaction scores are normally distributed. Use the appropriate T test with a significance level of 0.05 to test the hypothesis.
Research Question
Do the mean job satisfaction scores differ for men and women working in the hospital administration department?
Hypothesis
The mean job satisfaction scores do not differ for men and women working in the hospital administration department.
1. Compute an independent sample t test on these data. Report descriptive statistics (Mean and Standard deviation), t values, and p values.
2. Create a graph to show the differences between the two groups.
3. Write a Results section based on your analysis. Interpret results of the independent sample t test to answer the research question and the hypothesis. Use APA style for describing the results.
Submit the SPSS output file in a PDF to show the work you have done. Also submit a separate Word file describing the results in APA. Incorporate relevant table(s) and figure/graph(s) in the Word document formatted in APA style.
1
,
Data
Gender | Job satisfaction |
0 | 20 |
0 | 40 |
0 | 23 |
0 | 27 |
0 | 22 |
0 | 19 |
0 | 21 |
0 | 15 |
0 | 20 |
0 | 32 |
0 | 28 |
0 | 30 |
0 | 29 |
0 | 24 |
0 | 22 |
0 | 25 |
0 | 27 |
0 | 20 |
0 | 28 |
0 | 19 |
1 | 27 |
1 | 36 |
1 | 28 |
1 | 28 |
1 | 36 |
1 | 33 |
1 | 29 |
1 | 31 |
1 | 26 |
1 | 19 |
1 | 35 |
1 | 40 |
1 | 29 |
1 | 27 |
1 | 35 |
1 | 29 |
1 | 30 |
1 | 34 |
1 | 34 |
1 | 32 |
Legend
Gender |
Cheat |
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