I’ve reviewed a student's BSF2 report and want to recommend a few key considerations to all of you before you turn it in.
For a Null Hypothesis, she states: “There will be no difference between sex and confidence in banks and financial institutions in the United States.” Well, a better way to state it is: “There will be no difference between men and women in their confidence in banks and financial institutions in the U.S.” The difference in confidence (Y) is between two populations: men and women (X). Please review my latest blog on “Constructing Hypotheses” for a discussion on this subject in greater detail. Once you look at the ways I worded each type of hypothesis, review your work and make any necessary changes.
Fundamental to this assignment is the interpretation of each hypothesis you constructed. Did you accept or reject the null, for each? As tempting as it may be, how you decide has nothing to do with reading the percentage outcomes of the crosstabular tables. The only way to do it is to generate the Chi-Square Square statistic in SPSS (which we already covered in class and in your BSF2) and refer to and interpret the table(s) generated in SPSS. For example, if you examine the table below that was generated in SPSS, you can see TWO key pieces of information. As I state in your second BSF, focus on the Pearson Chi-Square value (in this table, it’s 5.77) and the significance of this X2 statistical outcome found under the ASYMP. SIG. (2-sided) column (in this table, it’s .450).
INTERPRETATION: If the identified significance level is less than or equal to .05, then you reject the null hypothesis of no difference and accept the research hypothesis which indicates that there is a difference. In this table, .450 is much greater than .05 (45% v. 5%), so you must accept the null hypothesis (at the same time, you’re rejecting both research hypotheses).
UPSHOT? That means that you should review all of your hypotheses interpretations based on each “Chi-Square Tests” table, like the one that appears below, and decide on which outcomes of your tested hypotheses should be accepted or rejected. Simply put, if the two-sided "asymp. sig." is less than or equal to .05, then reject the null hypothesis.
For a Null Hypothesis, she states: “There will be no difference between sex and confidence in banks and financial institutions in the United States.” Well, a better way to state it is: “There will be no difference between men and women in their confidence in banks and financial institutions in the U.S.” The difference in confidence (Y) is between two populations: men and women (X). Please review my latest blog on “Constructing Hypotheses” for a discussion on this subject in greater detail. Once you look at the ways I worded each type of hypothesis, review your work and make any necessary changes.
Fundamental to this assignment is the interpretation of each hypothesis you constructed. Did you accept or reject the null, for each? As tempting as it may be, how you decide has nothing to do with reading the percentage outcomes of the crosstabular tables. The only way to do it is to generate the Chi-Square Square statistic in SPSS (which we already covered in class and in your BSF2) and refer to and interpret the table(s) generated in SPSS. For example, if you examine the table below that was generated in SPSS, you can see TWO key pieces of information. As I state in your second BSF, focus on the Pearson Chi-Square value (in this table, it’s 5.77) and the significance of this X2 statistical outcome found under the ASYMP. SIG. (2-sided) column (in this table, it’s .450).
INTERPRETATION: If the identified significance level is less than or equal to .05, then you reject the null hypothesis of no difference and accept the research hypothesis which indicates that there is a difference. In this table, .450 is much greater than .05 (45% v. 5%), so you must accept the null hypothesis (at the same time, you’re rejecting both research hypotheses).
UPSHOT? That means that you should review all of your hypotheses interpretations based on each “Chi-Square Tests” table, like the one that appears below, and decide on which outcomes of your tested hypotheses should be accepted or rejected. Simply put, if the two-sided "asymp. sig." is less than or equal to .05, then reject the null hypothesis.
I hope this helps!
Professor Ziner
Professor Ziner
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