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The concept of Confidence Interval with example and illustrations The information is collected on public Net domain from the Elementary Statistics by Dr. Ghamsary, my own notes, and your text. It is for educational purpose only. Here is some information on the concept of Confidence Interval with example and illustrations. These solved problems clearly demonstrate the concept of Central Limit Theorem, z-table, and t-table.
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. (4 points) BUSI1013:STATISTICS FOR BUSINESS 5
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. (4 points) BUSI1013:STATISTICS FOR BUSINESS 6
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. (4 points) BUSI1013:STATISTICS FOR BUSINESS 7
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. (4 points) BUSI1013:STATISTICS FOR BUSINESS 8
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. (4 points) BUSI1013:STATISTICS FOR BUSINESS 9
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. (4 points) BUSI1013:STATISTICS FOR BUSINESS 10 The Z-table values are area under the curve [probability value, between 0 ~ 0.5]. Now, in t-table [given bellow], the table values are not area under the curve like in Z-case, but they are t-values only, and given for a specific degree of freedom [d.f. =N-1]. Now, it is making sense by looking at the t-table and using the given degree of freedom, d.f. [=N-1]. Take our calculated value and check, where it fits on that degree of freedom data line in the table. If our calculated value does not correspond to any value on that d.f. data line, then take the average of the 2 values that our calculated value falls in between. This then is your approximated calculated t-value in this table. Now, these 2 values that you chose, each corresponds to a tail value given on the top of the table. As you averaged the table values to get your approximated calculated t-value in the table, also average these corresponding tail values on the top of the table and this will be your p-value [this is the alpha value from the calculated value boundary line].