Variations in Z-Test and F-Test
Über den Vortrag
Der Vortrag „Variations in Z-Test and F-Test“ von Edu Pristine ist Bestandteil des Kurses „Archiv - Quantitative Analysis“. Der Vortrag ist dabei in folgende Kapitel unterteilt:
- Some variations in Z-test
- Two - Tailed Test
- Hypothesis testing for variances
- Test for single population variance
- Finding the critical value
- F-Test for difference in two population variances
- The F distribution
- Chebyshev's inequality
Dozent des Vortrages Variations in Z-Test and F-Test
Edu Pristine
Trusted by Fortune 500 Companies and 10,000 Students from 40+ countries across the globe, EduPristine is one of the leading International Training providers for Finance Certifications like FRM®, CFA®, PRM®, Business Analytics, HR Analytics, Financial Modeling, Operational Risk Modeling etc. It was founded by industry professionals who have worked in the area of investment banking and private equity in organizations such as Goldman Sachs, Crisil - A Standard & Poors Company, Standard Chartered and Accenture.EduPristine has conducted corporate training for various leading corporations and colleges like JP Morgan, Bank of America, Ernst & Young, Accenture, HSBC, IIM C, NUS Singapore etc. EduPristine has conducted more than 500,000 man-hours of quality training in finance.
http://www.edupristine.com
Kundenrezensionen
5,0 von 5 Sternen
| 5 Sterne |
|
5 |
| 4 Sterne |
|
0 |
| 3 Sterne |
|
0 |
| 2 Sterne |
|
0 |
| 1 Stern |
|
0 |
Auszüge aus dem Begleitmaterial
... US$19,000 and hence would not have the buying power for the course? They would perceive the training to be of inferior quality, if their household income is > US$19,000 and hence not buy the training? How would the decision criteria change? What should be the testing strategy? Hint: From the question wording infer: Two tailed testing ...
... (Confidential) tailed testThe lower boundary = Conclusion: If the household income lies between $18,216 and $19,784 then the student will attend the course at 95% confidence ...
... sample size is small. Let the sample size, n = 25, X = $20,000, s = $8,00 0 From the t-table t c= 1.71 for ?= 0.05 and d.f. = 24 Decision rule: “Reject H 0 if t >1.7l.” Points to observe: You could not launch ...
... the testing strategy? Use two means hypothesis: ? c= ? n Which can also be reduced to ? c– ? n= 0 The only treatment to be made different is that the standard error has to be calculated as: The rest of the treatment remains the same as one mean hypothesis. Why is it possible to use the ...
... Since we are checking for significance difference on both the ends, so it’s a two tailed test ...
... Specifications from the company call for a standard deviation of not more than 2 degrees (or variance of 4 degrees ...
... = Variance of Sample 1 (n1 – 1) = numerator degrees of freedom = Variance ...
... two appropriate degrees of freedom. One for numerator and other for denominator In the F table: Numerator degrees of freedom determine the row ...
... Do not reject H0 Reject H0 F0 Rejection region for a one-tail test is: (When the larger sample variance in the numerator) ...
... between stocks listed on the Dow30 & EURO STOXX 50. You collect the following data: Is there a difference in the variances between the Dow30 ...
... critical value for ?= 0.05 Numerator: df 1= n 1– 1 = 30 – 1 = 29 Denominator: ...
... standard deviations of the mean. Where k is any positive real ...
