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PLANNING COMMITTEE MINUTES 12013 9:30 am Wednesday, September 5, 2012, Council Chambers Hamilton City Hall 71 Main Street West Present: Councillors B. Clark (Chair), J. Far (1st Vice Chair), B. Johnson
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How to fill out pearson and t

How to fill out pearson and t:
01
Start by gathering the necessary data. Pearson and t-tests are statistical tests that require a set of quantitative data. Make sure you have collected the relevant data points for your analysis.
02
Determine the type of analysis you want to perform. Pearson correlation is used to measure the relationship between two continuous variables, while t-test is used to compare the means of two groups. Understand the objective of your analysis and choose the appropriate test accordingly.
03
Calculate Pearson correlation coefficient. If you are performing a Pearson correlation analysis, you need to compute the correlation coefficient. This can be done using statistical software such as SPSS or Excel. Input the data and specify the variables you want to correlate. The output will provide you with the correlation coefficient, as well as p-value indicating the significance of the correlation.
04
Interpret the results. After obtaining the correlation coefficient and p-value, interpret the findings based on your research question. A correlation coefficient ranges between -1 and 1, where values close to -1 or 1 indicate a strong relationship, while values close to 0 suggest a weak or no relationship. The p-value helps determine the significance of the correlation. Generally, a p-value less than 0.05 is considered statistically significant.
05
Conduct a t-test. If you are performing a t-test, start by identifying the two groups you want to compare. This could be two different populations, treatment groups, or any other relevant groups. Input the data into statistical software, specify the variables representing each group, and choose the appropriate t-test (independent samples t-test, paired samples t-test, etc.).
06
Analyze the t-test results. The output of a t-test will provide you with the t-value and p-value. The t-value indicates the difference between the means of the two groups, while the p-value determines the significance of this difference. Similar to Pearson correlation, a p-value less than 0.05 is typically considered statistically significant.
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In conclusion, mastering the process of filling out Pearson and t-tests is beneficial for researchers, data analysts, and students alike. Understanding the steps involved and knowing who can benefit from these tests allows individuals to make informed decisions and draw meaningful conclusions from their data analysis.
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