Thank you for the detailed explanation. Please, what inferential analysis method would you suggest to test a hypothesis that seeks to measure the influence of an independent variable on a dependent variable among the same group of respondents. For example, assume that 50 respondents are asked about their opinions on both the independent variable and the dependent variable, and you want to determine how their answers of the independent variable influence that of the dependent variable. Independent T-test or Paired-t-test?
Since you have 1 independent variable and 1 dependent variable and wish to establish how the independent variable influences the dependent variable, you will simply conduct a Simple Linear Regression. Convert the Likert scale data to continuous variables before performing Linear Regression. This video will help you th-cam.com/video/p4TEVkL_BMc/w-d-xo.html
16:24 A shopping mall conducts a survey to assess the customer's satisfaction which also include a statement "would you like having separate shopping section for personal hygine related products for women." 90% respondents check option 5 "strongly agree". If the mall administration decides to provide separate section for women hygine products which turn outs to increase sales in this area isn't a decision/conclusion based on descriptive statistics? Sir your comment please.
If you just want to describe people's opinions only, descriptive statistics can be used. But if you want to establish that customers' satisfaction with the shopping mall's HR team response to complaints would increase product sales, then, you cannot use descriptive statistics to achieve this. You need to conduct inferential statistics to achieve this. Remember that as 90% of your respondents strongly agreed, the remaining 5% either disagreed, strongly disagreed or neutral. If you make decision based on the 90% (i.e., majority carries the vote), how will you interpret the remaining 5%? This is the issue with descriptive statistics. With inferential statistics, such questions do not arise given that you'll convert all responses to continuous variable and then, test your postulations.
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Thank you for the detailed explanation. Please, what inferential analysis method would you suggest to test a hypothesis that seeks to measure the influence of an independent variable on a dependent variable among the same group of respondents. For example, assume that 50 respondents are asked about their opinions on both the independent variable and the dependent variable, and you want to determine how their answers of the independent variable influence that of the dependent variable. Independent T-test or Paired-t-test?
Since you have 1 independent variable and 1 dependent variable and wish to establish how the independent variable influences the dependent variable, you will simply conduct a Simple Linear Regression. Convert the Likert scale data to continuous variables before performing Linear Regression. This video will help you
th-cam.com/video/p4TEVkL_BMc/w-d-xo.html
16:24
A shopping mall conducts a survey to assess the customer's satisfaction which also include a statement "would you like having separate shopping section for personal hygine related products for women."
90% respondents check option 5 "strongly agree".
If the mall administration decides to provide separate section for women hygine products which turn outs to increase sales in this area isn't a decision/conclusion based on descriptive statistics?
Sir your comment please.
If you just want to describe people's opinions only, descriptive statistics can be used. But if you want to establish that customers' satisfaction with the shopping mall's HR team response to complaints would increase product sales, then, you cannot use descriptive statistics to achieve this. You need to conduct inferential statistics to achieve this.
Remember that as 90% of your respondents strongly agreed, the remaining 5% either disagreed, strongly disagreed or neutral. If you make decision based on the 90% (i.e., majority carries the vote), how will you interpret the remaining 5%? This is the issue with descriptive statistics.
With inferential statistics, such questions do not arise given that you'll convert all responses to continuous variable and then, test your postulations.
My minimum varies some variable is 3 and some is 1. Is it correct ? Please help!
Sure, there is no strong rule on this.