Important MCQs on Experimental Design 1

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The post is about MCQs on Experimental Design with Answers. There are 20 multiple-choice questions. The quiz is related to the Basics of the Design of Experiments, Analysis of variation, assumptions of ANOVA, One-Way ANOVA, Single-factor designs, and Two-Way ANOVA. Let us start with the MCQs on Experimental Design Quiz.

MCQs about Designs of Experiment

1. In two-way ANOVA with $m=5$, $n=4$, then the total degrees of freedom is

 
 
 
 

2. An experiment is performed in CRD with 10 replications to compare two treatments. The total experimental units will be

 
 
 
 

3. In one-way ANOVA, with the usual notation, the error degree of freedom is

 
 
 
 

4. In ANOVA we use

 
 
 
 

5. Analysis of variance is used to test

 
 
 
 

6. If the treatments consist of all combinations that can be formed from the different factors then the experiment is

 
 
 
 

7. In one-way ANOVA with the total number of observations is 15 with 5 treatments then the total degrees of freedom is

 
 
 
 

8. Consider an experiment to investigate the efficacy of different insecticides in controlling pests and their effects on subsequent yield. What is the best reason for randomly assigning treatment levels (spraying or not spraying) to the experimental units (farms)?

 
 
 
 

9. The assumption used in ANOVA is

 
 
 
 

10. In one-way ANOVA, the calculated F value is less than the table F value then

 
 
 
 

11. In one-way ANOVA, given $SSB = 2580, SSE =1656, k = 4, n = 20$ then the value of F is

 
 
 
 

12. A teacher uses different teaching ways for different groups in his class to see which yields the best results. In this example a treatment is

 
 
 
 

13. A Mean Square is

 
 
 
 

14. If there are 6 treatments with 3 blocks in a RCBD then the degrees of freedom for error are

 
 
 
 

15. Analysis of variance

 
 
 
 

16. If the total degrees of freedom between treatments in a CRD are 15 and 4 respectively, the degrees of freedom for error will be

 
 
 
 

17. Consider $k$ independent samples each containing $n_1, n_2, \cdots, n_k$ items such that $n_1+n_2+\cdots+ n_k=n$. In ANOVA we use F-distribution with a degree of freedom

 
 
 
 

18. Which of the following are important in designing an experiment?

 
 
 
 

19. In two-way ANOVA with $m$ rows and $n$ columns, the error degrees of freedom is

 
 
 
 

20. For a single-factor ANOVA involving five populations, which of the following statements is true about the alternative hypothesis?

 
 
 
 


Online MCQs on Experimental Design

MCQs on Experimental Design Quiz
  • Analysis of variance is used to test
  • The assumption used in ANOVA is
  • In ANOVA we use
  • Consider $k$ independent samples each containing $n_1, n_2, \cdots, n_k$ items such that $n_1+n_2+\cdots+ n_k=n$. In ANOVA we use F-distribution with a degree of freedom
  • In one-way ANOVA, with the usual notation, the error degree of freedom is
  • In one-way ANOVA, given $SSB = 2580, SSE =1656, k = 4, n = 20$ then the value of F is
  • In two-way ANOVA with $m$ rows and $n$ columns, the error degrees of freedom is
  • In one-way ANOVA, the calculated F value is less than the table F value then
  • In two-way ANOVA with $m=5$, $n=4$, then the total degrees of freedom is
  • In one-way ANOVA with the total number of observations is 15 with 5 treatments then the total degrees of freedom is
  • If the treatments consist of all combinations that can be formed from the different factors then the experiment is
  • Consider an experiment to investigate the efficacy of different insecticides in controlling pests and their effects on subsequent yield. What is the best reason for randomly assigning treatment levels (spraying or not spraying) to the experimental units (farms)?
  • Which of the following are important in designing an experiment?
  • Analysis of variance
  • A Mean Square is
  • For a single-factor ANOVA involving five populations, which of the following statements is true about the alternative hypothesis?
  • An experiment is performed in CRD with 10 replications to compare two treatments. The total experimental units will be
  • A teacher uses different teaching ways for different groups in his class to see which yields the best results. In this example a treatment is
  • If the total degrees of freedom between treatments in a CRD are 15 and 4 respectively, the degrees of freedom for error will be
  • If there are 6 treatments with 3 blocks in a RCBD then the degrees of freedom for error are
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Best MCQs Time Series Analysis 1

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The post is about MCQs Time Series Analysis. There are 20 multiple-choice questions related to time series data, components of time series, least square method, objective of times series, differencing time series, decomposing a time series, and log transformation. Let us start with the MCQs time series analysis.

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MCQs Time Series Analysis

MCQs Time Series Analysis
  • A time series data is a set of data recorded at
  • The time series analysis helps:
  • A time series consists of ————.
  • The forecasts on the basis of a time series are ————-.
  • The component of a time series attached to long-term variations is termed as ————.
  • The sales of a shopkeeper are associated with the component of a time series
  • The secular trend is indicative of long-term variation towards
  • The linear trend of a time series indicates towards ———–.
  • The method of least squares to fit in the trend is applicable only if the trend is ————.
  • The sequence which follows an irregular or random pattern of variation is called ————.
  • Three are ———– main components of a time series.
  • The systematic components of a time series which follow regular pattern of variations are called
  • Which of the following is an example of irregular variation?
  • If a straight line is fitted to the time series, then
  • What is autocorrelation in time-series analysis?
  • In time-series analysis, what does “T” typically represent?
  • What is the primary objective of differencing in time-series transformation?
  • What is the purpose of log transformation in time-series analysis?
  • What is the key objective of decomposing a time series in time-series analysis?
  • What technique is commonly used for handling seasonality in time-series feature engineering?
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Important MCQs Index Numbers 1

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The post is about MCQs index numbers. There are 20 multiple-choice questions related to the basics of index numbers, price relative, fixed base method, chain base methods, weighted index numbers, Paasche’s index numbers, Laspeyrs index numbers, and Fisher Idea index numbers. Let us start with the MCQs Index Numbers Quiz.

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MCQs Index Numbers

MCQs Index Numbers
  • The index number that can be used for multi-purpose is:
  • An index number computed for a single commodity is called
  • The ———- index number has a wide scope
  • The price relative formula is $\frac{?}{P0}\times 100$
  • The index for the base period is always taken as
  • In the fixed base method, the base period should be
  • The commodities subject to considerable price variations can be best measured by
  • In the chain base method, the base period is
  • The chaining process used to make a comparison of the index number is
  • Price relatives computed for the chain base method are called
  • The most suitable average for index numbers is
  • Index numbers are free from a unit of measurement because the index number shows
  • Long-term variations are regarded as
  • Paasche’s price index number is also called
  • The index number having an upward bias is
  • The index give by $\frac{\sum p_n q_n}{\sum p_0 q_0}\times 100$
  • If Laspeyre’s index number is 200, and Paasche’s index number is 200 then the Fisher index number will be
  • Increased demand for coolers in summer and heaters in winter is an example of
  • The price used in the construction of consumer price index numbers is
  • ——— method uses quantities consumed in the base period when computing a weighted index
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Important MCQ Random Variables 1

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 The post is about MCQ Random Variables. There are 20 multiple-choice questions related to random experiments, random variables and types of random variables, expectations, discrete random variables, and continuous random variables. Let us start with the MCQ Random Variables Quiz.

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MCQ Random Variables Quiz

MCQ Random Variables Quiz
  •  If $X$ is a continuous random variable, then function $f(X)$ is
  • A variable (Random Variable) assuming an infinite number of values is called
  • A variable whose value is determined by the outcome of a random experiment is called
  • If $X$ and $Y$ are random variable then $E(X + Y)$ is equal to
  • If $X$ is a discrete random variable, the function $f(X)$ is
  • When four coins are tossed, the value of a random variable (Numbers of head) is
  • A variable (Random Variable) assuming a finite number of values is called
  • If $X$ and $Y$ are independent random variables then $E(XY)$ is equal to
  • Two random variables $X$ and $Y$ are said to be independent if:
  • If $X$ and $Y$ are two independent variables, then
  • A continuous random variable is a random variable that can
  • If $X$ is a random variable that can take only non-negative values, then
  • For a random variable $X$, $E(X)$ is
  • If $C$ is a non-random variable, the $E(C)$ is
  • A continuous variable is a variable that can assume
  • A ———– random variable has a countable number of possible values.
  • Which of the following statements accurately describes a key difference between discrete and continuous random variables?
  • Which of the following are examples of discrete random variables?
  • Which of the following statements describes continuous random variables?
  • If $X$ is a random variable and $a$ and $b$ are constants then $Var(aX+ b)$ is equal to
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