The concept of Confidence Interval with example and illustrations The

The concept of confidence interval with example and

This preview shows page 4 - 11 out of 11 pages.

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.
Image of page 4
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. ( 4 points ) BUSI 1013: S TATISTICS FOR B USINESS 5
Image of page 5
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. ( 4 points ) BUSI 1013: S TATISTICS FOR B USINESS 6
Image of page 6
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. ( 4 points ) BUSI 1013: S TATISTICS FOR B USINESS 7
Image of page 7
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. ( 4 points ) BUSI 1013: S TATISTICS FOR B USINESS 8
Image of page 8
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. ( 4 points ) BUSI 1013: S TATISTICS FOR B USINESS 9
Image of page 9
5. Use the data in BUSI1013 Bank Dataset.xlsx (from Unit 1 Exercise Question 2) to answer this question. ( 4 points ) BUSI 1013: S TATISTICS FOR B USINESS 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].
Image of page 10
Image of page 11

You've reached the end of your free preview.

Want to read all 11 pages?

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture