Basic Statistics and Data Analysis

Lecture notes, MCQS of Statistics

MCQ Hypothesis Testing 1

Multiple Choice Questions from Statistical Inference for the preparation of exam and different statistical job tests in Government/ Semi-Government or Private Organization sectors. These tests are also helpful in getting admission in different colleges and Universities.

Most of the MCQs on this page are covered from Estimate and Estimation, Testing of Hypothesis, Parametric and Non-Parametric tests etc.

 

Q1: A quantity obtained by applying certain rule or formula is known as

A) Sample
B) Test Statistics
C) Estimate
D) Estimator
E) Estimation

Q2: Criteria to check a point estimator to be good are

A) Consistency
B) Unbiasedness
C) Efficiency
D) All Above

Q3: $1 – \alpha$ is the probability of

A) Type-I Error
B) Rejection Region
C) Acceptance Region
D) Type-II Error

Q4: Parameter is a ————- quantity

A) Constant
B) Variable
C) Non of the above

Q5: Consistency of an estimator can be checked by comparing

A) Mean
B) Mean Square
C) Variance                correct
D) Standard Deviation

Q6: If we reject the null hypothesis, we might be making
A) Type-I Error
B) Type-II Error
C) A correct Decision
D) Unpredictable

Q7: Herbicide A has been used for years in order to kill a particular type of weed. An experiment is to be conducted in order to see whether a new herbicide, Herbicide B, is more effective than Herbicide A. Herbicide A  will continue to be used unless there is sufficient evidence that Herbicide B is more effective. The alternative hypothesis in this problem is

A) Herbicide A is more effective than Herbicide B
B) Herbicide B is more effective than Herbicide A    correct
C) Herbicide A is not more effective than Herbicide B
D) Herbicide B is not more effective than Herbicide A

Q8: Analysis of Variance (ANOVA) is a test for equality of

A) Variances
B) Means
C) Proportions
D) Only two Parameters

Q9: Which of the following is an assumption underlying the use of the t-distributions?

A) The variance of the population is known
B) The samples are drawn from a normally distributed population.
C) s (sample standard deviation) is an unbiased estimate of the population variance.
D) All Above

Q10: For t distribution, increasing the sample size, the affect will be on

A) Degrees of Freedom
B) The t-ratio
C) Standard Error of the Means
D) All Above

Q11: The t distributions are

A) Same as Normal Curve
B) Skewed
C) Symmetrical
D) None of these

Q12: Condition for applying Central Limit Theorem (CLT) which approximate the sampling distribution of the mean with a normal distribution is?

A) N<30
B) n/N > 5
C) N(1-P)>5
D) N>30
E) 2n<N

Q13: Which of the following is a true statement, for comparing the t distributions with standard normal,

A) The Normal Curve is symmetrical whereas the t-distributions are slightly skewed
B) The proportion of area beyond a specific value of “t” is less than the proportion of normal curve
C) Greater the degree of freedom, the more the t-distribution resembles the standard normal distribution
D) None of the Above

Q14: What is the probability of a type II error when α=0.05?

A) 0.025
B) 0.05
C) o.95
D) Cannot be determined without more information

Q15: The critical value of a test statistic is determined from

A) Calculations from the data
B) Calculations based on many actual repetitions of the same experiment
C) The sampling distribution of the statistic assuming Alternative Hypothesis
D) The sampling distribution of the statistics assuming Null Hypothesis

 

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MCQS about Statistical Inference

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The Author

Muhammad Imdadullah

Student and Instructor of Statistics and business mathematics. Currently Ph.D. Scholar (Statistics), Bahauddin Zakariya University Multan. Like Applied Statistics and Mathematics and Statistical Computing. Statistical and Mathematical software used are: SAS, STATA, GRETL, EVIEWS, R, SPSS, VBA in MS-Excel. Like to use type-setting LaTeX for composing Articles, thesis etc.

8 Comments

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  1. ANOVA IS a test for comperison of several mean
    question # 8 ans is wrong

    1. again see, check word quality

    2. ANOVA is a test for comperison of two or more means but its stands for “Analysis of variance” .Its make me confused…would you like to define it please…?

      1. group Means are compared on the basis of their variances.

    3. You see a book. How could you so confident to say anova is used to compare variance when you are a phd student? very strange!!

      1. The comment is also too strange. To Err is human. However, correction is made.
        It is not easy to write and update the content, especially the options related work.
        Anyhow
        Thanks

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