Statistical Inteference and Hypothesis testing von Edu Pristine

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Über den Vortrag

Der Vortrag „Statistical Inteference and Hypothesis testing“ von Edu Pristine ist Bestandteil des Kurses „Archiv - Quantitative Analysis“. Der Vortrag ist dabei in folgende Kapitel unterteilt:

  • Hypothesis testing
  • Statistical interference
  • Properties of point estimators
  • Launching a niche course for MBA students?
  • Identifying the critical sample Mean value
  • PD's criterion for decision making
  • Computing the criterion value
  • Test statistic
  • Errors in estimation
  • P-Value - Actual significance level
  • Questions

Dozent des Vortrages Statistical Inteference and Hypothesis testing

 Edu Pristine

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


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... Inference Hypothesis Testing Type I Errors, Type II ...

...Finding out estimator values (mean, variance etc) of the sample Hypothesis testing: Judge whether the hypothesis ma de ...

...experimental data Null-hypothesis testing answers the question: “How well the findings fit the possibility that chance factors alone might be responsible". Example:...

...estimator: Considering only the unbiased estimators of a parameter, the one which has least variance is called the efficient estimator Consistent estimator: ...

...the students would be very hot in job market. He meets a random sample of 100 students and discovers the following characteristics of the market. Mean household income to $20,000. Interest level in students = high. Current knowledge of students for the niche concepts = low Christos strongly believes the course would adequately profitable in students if they have the buying power for the course. They would be ...

...is equivalent to either accepting or rejecting the hypothesis: EduPristine (Confidential). The population mean household income in the new market area is greater than $19,000 The term one-tailed signifies that all z-values that would ...

...EduPristine (Confidential) Sample mean values greater than $19,000--that is x- values on the right-hand side of the sampling distribution centered ...

...(Confidential) z c = 1.645. Substitute the values of z c, s, and (under the assumption that H 0 is "just" true ) x c = + z cs ...

...In this case, since the observed sample EduPristine (Confidential) = $19,000 Z = 0 X = $20,000 Z = 2.5 ...

...Correct Decision Confidence Level = 1-? Type-II Error P(Type-II Error) = ? His False Type-I Error Significance Level = ? Power=1-? EduPristine (Confidential). Type I error occurs if the null hypothesis is rejec ted when it is true. Type II error occurs if the ...

... mean is only $19,000 = 0.00621. This value is sometimes called the actual significance level, or the p-value. Calculated probability of rejecting the null hypothesis (H) when that hypothesis (H) = 0.05. EduPristine (Confidential) ...

...III.Type I error is the error when a false null hypothesis is not rejected IV.Systematic error is caused by non-random variations due to unknown sources ...

...in the level of Type-I error increases the Type-II error ...

...would be 99% confidence interval for the mean score on the exam for the 6400 candidates who study at least 250 hours (Given Z 0.005 ...

...interval: ? ± Z * (?/sqrt(n)) = ...