Help with statistical technique for research

In summary, a student is conducting an experimental report in their Social Psychology class on the lack of females in engineering and other math-intensive fields. They surveyed men and women's life interests, values, and attitudes towards gender roles, using a four-point scale. The student is unsure of which statistical technique to use for their research and is seeking advice on whether to use Chi-square, correlation, or other methods. They also need guidance on how to analyze their data, but have not yet studied Statistics or Research Methods. It is recommended that the student first determine the hypotheses they wish to test and the parameters they want to estimate, and then decide between Hypothesis Testing and Estimation for their statistical analysis. It is noted that the statistical analysis should be
  • #1
Ilikecereal
17
1
I am supposed to do an experimental report in my Social Psychology class. I am analyzing the factors affecting the lack of females in engineering and other math-intensive fields. I measured men and women's life interests, life values and attitudes to gender roles in our survey because I think that these factors contribute to the lack of women. Perhaps women are just not that interested in these fields compared to men, perhaps these fields are incompatible with their values in life (for eg. not having to work for extremely long hours) or maybe they weren't as encouraged to go into these fields as their male counterparts. I used a four point scale for my survey. (Not Interested-Very Interested and Strongly Agree-Strongly Disagree)

The problem is, I have not studied Statistics or Research Methods yet. I am a completely lost as to how to go about this. Can someone please tell me what statistical technique would be appropriate for this research? Chi-square? Correlation? Other methods? If anyone can just provide a basic outline as to how I would go about analyzing my data, that would be very helpful.
 
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  • #2
A basic lesson in the statistical analysis of experiments is that the statistical analysis should be planned before the experiments are completely designed and conducted.

Given it's too late for that, you should decide which of the two main topics in statistics apply. These are 1) Hypothesis Testing and 2) Estimation. What hypotheses do you wish to test? What parameters of the phenomenon do you wish to estimate?
 

Related to Help with statistical technique for research

What is a statistical technique?

A statistical technique is a method used to analyze and interpret data in order to make inferences and draw conclusions. It involves the use of mathematical formulas and tools to analyze and understand patterns in data.

Why is statistical technique important in research?

Statistical techniques are important in research because they allow researchers to make sense of large amounts of data and draw meaningful conclusions. They help to identify relationships and patterns in data and determine the significance of these findings.

What are some common statistical techniques used in research?

Some common statistical techniques used in research include regression analysis, t-tests, ANOVA, chi-square tests, and correlation analysis. These techniques can be used to analyze both quantitative and qualitative data.

How do I choose the right statistical technique for my research?

The choice of statistical technique will depend on the type of data you have, the research question you are trying to answer, and the level of measurement of your variables. It is important to consult with a statistician or do thorough research to determine the most appropriate technique for your specific research project.

Can I use more than one statistical technique in my research?

Yes, it is common for researchers to use multiple statistical techniques in their research. This can help to validate findings and provide a more comprehensive understanding of the data. However, it is important to consider the potential biases and limitations of each technique and use them appropriately.

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