ELEM STAT INFERENCE
ELEM STAT INFERENCE STAT 201
Popular in Course
Popular in Statistics
This 2 page Class Notes was uploaded by Darien Kutch on Wednesday October 21, 2015. The Class Notes belongs to STAT 201 at Texas A&M University taught by Staff in Fall. Since its upload, it has received 25 views. For similar materials see /class/225764/stat-201-texas-a-m-university in Statistics at Texas A&M University.
Reviews for ELEM STAT INFERENCE
Report this Material
What is Karma?
Karma is the currency of StudySoup.
Date Created: 10/21/15
Review Questions for 2E Mid term exam 1 You are interested in the eating habits of college freshmen The following table describes the probability distribution of the number of Ramen Noodles consumed by a college freshman in a day X 0 1 2 3 4 PX 02 01 009 001 What is the probability that two randomly selected freshmen both ate an odd number of packages yesterday A 004 B 0084 C 029 D 058 S0111 POdd P1 P3 02 009 029 POdd and Odd POddPOdd 029029 0084 2 Sample proportion is an example of A parameter B Statistic C neither S0111 B 3 EX 3 EY2 Define a new random variable ZXY and another random variable WXY What is EZW A 6 B 5 C 1 D None ofthe above 0111 EZWEXYXYE2X2EX6 4 Let X be a random variable denoting number accidents occurring per day in Bryan in the month of August Let EX 3 Let X1 denotes the number accidents occurred in Aug 1 X2 denotes the noof accidents occurred in Aug2 and so on till X31 denoting number of accidents occurring in Aug31 Let M be mean of daily accidentie M X1X2X3X3131 Find EM A 3 B 331 C Cannot be computed 0111 A Law of large number implies that sample mean is an unbiased estimator of population mean that means EM opulation mean EX3 5 Which of the following is are true A All parameters have a sampling distribution since they vary from sample to sample B Parameters are usually unknown and are required to be estimated C Random chance will cause a parameter to vary from sample to sample D Two of the above are true E None of the above is true S0111 B from the definition of parameters 6 If a statistic is highly biased then it is also shows high variability 2 A Yes B No C May be S0111 C Bias has nothing to do with variability An estimator can be unbiased but can show high variability and viceversa 7 Suppose we compared the decibel levels of the four di erent speaker brands each with a di erent measuring instrument This is an example of A Bias B Variability C Confounding D None of above S0111 Confounding Since the effect of dilTerent measuring instruments will get confounded in measuring the decibel levels for di erent brands 8 First divide the population into several sections Then take a simple random sample of these sections The final sample would consist of all the individuals in the selected sections This is an example of A Simple RS B Stratified RS C Cluster RS D Two stage Sample D None of them S0111 Cluster Random Sampling from definition 9 When an individual chosen for the sample cannot be contacted then occurs A Undercoverage B Non response C Response Bias D None of them S0111 Non response From definition Differentiate between non response and response bias The latter occurs when the respondent deliberately resorts to lying while the former occurs when the respondent simply refuses to answer 10 Let the set Al2 and set B34 What is PA and B A 0 B 12 12 C l D Cannot be computed S0111 0 Note A and B are disjoint So A f B empty set Then use the formula that Pempty set0