Important MCQs Chi Square Test – 2

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This post is about Online MCQs on the Chi Square Test. The MCQs Chi Square test covers the topic of attributes, degrees of freedom, coefficient of association, Chi-Square Distribution, observed and expected frequencies of attributes, etc. Let us start with the MCQs Chi Square Test of Association.

MCQs about Association between the attributes.

1. The process of dividing the objects into two mutually exclusive classes is called

 
 
 
 

2. For a $4\times 5$ contingency table, there are

 
 
 
 

3. In Chi-Square association, the presence of an attribute is denoted by

 
 
 
 

4. The eye color of 100 men is an example of

 
 
 
 

5. The value of $\chi^2$-square distribution cannot be

 
 
 
 

6. Two attributes $A$ and $B$ are said to be positively associated if

 
 
 
 

7. If $\chi^2=5.8$ and $d.f.=1$, we make the following decision

 
 
 
 

8. Two attributes $A$ and $B$ are said to be independent if

 
 
 
 

9. When Chi-Square ($\chi^2=0$), the attributes are

 
 
 
 

10. A characteristic that varies in quality from one individual to another is called

 
 
 
 

11. For a $2\times 2$ contingency table, the degrees of freedom is

 
 
 
 

12. The range of $\chi^2$ is

 
 
 
 

13. If $AB<\frac{(A)(B)}{N}$ then the association between two attributes $A$ and $B$ is

 
 
 
 

14. The Chi-Square test for a $2\times 2$ contingency table is not valid unless

 
 
 
 

15. Association is a measure of the strength of the relationship between

 
 
 
 

16. For a $r \times c$ contingency table, the Chi-Square test has d.f.?

 
 
 
 

17. The number of parameters in the Chi-Square distribution is

 
 
 
 

18. For a $3\times 3$ contingency table, the degrees of freedom is

 
 
 
 

19. The parameter of Chi-Square distribution is

 
 
 
 

20. If for a contingency table, $df=12$ and the number of rows is 4 then the number of columns will be

 
 
 
 


The relationship/ Dependency between the attributes is called association and the measure of degrees of relationship between the attributes is called the coefficient of association. The Chi-Square Statistic is used to test the association between the attributes. The Chi-Square Association is defined as

$$\chi^2 = \sum \frac{(of_i – ef_i)^2}{ef_i}\sim \chi^2_{v},$$

where $v$ denotes the degrees of freedom

Attributes are said to be independent if there is no association between them. Independence means the presence or absence of one attribute does not affect the other. The association is positive if the observed frequency of attributes is greater than the expected frequency and negative association or disassociation (negative association) is if the observed frequency is less than the expected frequency.

MCQs Chi Square Test

  • A characteristic that varies in quality from one individual to another is called
  • The eye color of 100 men is an example of
  • Association is a measure of the strength of the relationship between
  • In Chi-Square association, the presence of an attribute is denoted by
  • The process of dividing the objects into two mutually exclusive classes is called
  • The number of parameters in the Chi-Square distribution is
  • The parameter of the Chi-Square distribution is
  • The value of $\chi^2$-square distribution cannot be
  • The range of $\chi^2$ is
  • Two attributes $A$ and $B$ are said to be independent if
  • Two attributes $A$ and $B$ are said to be positively associated if
  • If $AB<\frac{(A)(B)}{N}$ then the association between two attributes $A$ and $B$ is
  • If $\chi^2=5.8$ and $d.f.=1$, we make the following decision
  • For a $4\times 5$ contingency table, there are
  • For a $r \times c$ contingency table, the Chi-Square test has d.f.?
  • If for a contingency table, $df=12$ and the number of rows is 4 then the number of columns will be
  • For a $3\times 3$ contingency table, the degrees of freedom is
  • For a $2\times 2$ contingency table, the degrees of freedom is
  • When Chi-Square ($\chi^2=0$), the attributes are
  • The Chi-Square test for a $2\times 2$ contingency table is not valid unless
MCQs Chi-Square Test

Perform another Non-Parametric Test: MCQs Non-Parametric

R Frequently Asked Questions

Statistics Data Analysis Project (2021)

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The main objective of the “Statistics Data Analysis Project” is to learn how to analyze and interpret the data. All the submitted videos will be compiled into one video file and it will be shared with each participant and different social platforms. The video will also be uploaded on YouTube. All participants’ names and their relevant provided information will be marked on their videos.

This data set contains information on 78 people using one of three diets.  A short description of the variable is given below.

Variable NameVariable LabelData Type
PersonParticipant number 
genderGender, 1 = male, 0 = femaleBinary
AgeAge (years)Scale
HeightHeight (cm)Scale
preweightWeight before the diet (kg)Scale
DietDietCategorical
weight10weeksWeight after 10 weeks (kg)Scale
weightLOSTWeight lost after 10 weeks (kg)Scale

What to do with data:

  • You need to perform possible statistical analysis (data visualization, descriptive, and inferential) on this data using any statistical software.
  • You may check statistical assumptions for data and different inferential tests.
  • You may create new variables or recode the variables to perform different statistics.
  • You also need to briefly describe the results obtained.
  • You may record your audio for explanation purposes or may insert text using and text editor.
  • For audio recording you may use your local language too, however preference is Urdu or English language.
Statistics Data Analysis Project

What will you learn:

  1. You will learn the use of different statistical software with a live demonstration of the procedure
  2. You will learn how to perform the required statistical analysis on different types of data sets or variables.
  3. You will learn how to interpret the results.
  4. You will learn what must be done before performing any statistical analysis
  5. You may also learn how to report or publish your results.

Statistics Data Analysis Project Requirements

  1. You need to record the video of whatever you do with data. For example, import of data file, setting of variable properties, step-by-step procedure of performing any required statistical analysis (such as descriptive statistics, t-test, and possible graphs, etc.)
  2. Each participant will submit only one file.
  3. For video recording, you can use any screen recording software. You can use ‘Sharex’ or ‘apowersoft’ screen recorder software’ too.
  4. The total time of video must not exceed 10 minutes.
  5. The file type should be mp4 with H.264/ H.265
  6. The resolution may be ‘640 x 480’, ‘1280 x 720’, and 1920 x 1080’
  7. You will email me (at mimdadasad@gmail.com) the Google Drive or Dropbox link of your ‘screen recorded video’ file.
  8. For help with Statistical Software, you can visit: https://itfeature.com/statistical-softwares

Who Should Participate:
Any student, researcher, or teacher of Statistics

Download Data File:

Diet-DataDownload

Note: The pure objectivity of the “Statistics Data Analysis Project” is to promote the subject of Statistics in Pakistan.

https://itfeature.com

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Introduction to R Language

Important MCQs Skewness and Kurtosis 11

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This quiz contains MCQs Skewness and Kurtosis covering the shape of the distribution, Measures of central tendency such as mean, median, mode, Weighted mean, data and type of data, sources of data, Measures of Dispersion/ Variation, Standard Deviation, Variance, Range, and measure of position, etc. Let us start the MCQs Skewness and Kurtosis Quiz.

Please go to Important MCQs Skewness and Kurtosis 11 to view the test

If you found that any POSTED MCQ is/ are WRONG
PLEASE COMMENT below the MCQ with the CORRECT ANSWER and its DETAILED EXPLANATION.

Don’t forget to mention the MCQs Statement (or Screenshot), because MCQs and their answers are generated randomly

Basic statistics deals with the measure of central tendencies (such as mean, median, mode, weighted mean, geometric mean, and Harmonic mean) and measures of dispersion (such as range, standard deviation, and variances).

Basic statistical methods include planning and designing the study, collecting data, arranging, and numerical and graphically summarizing the collected data.

Basic statistics are also used to perform statistical analysis to draw meaningful inferences.

MCQs Skewness and Kurtosis

A basic visual inspection of data using some graphical and numerical statistics may reveal useful hidden information already available in the data. The graphical representation includes a bar chart, pie chart, dot chart, box plot, etc.

Companies related to finance, communication, manufacturing, charity organizations, government institutes, simple to large businesses, etc. are all examples that have a massive interest in collecting data and measuring different sorts of statistical findings. This helps them to learn from the past, noticing the trends, and planning for the future.

Various graphical and numerical ways are used to check the skewness of the data. Skewness is the lack of symmetry in distribution.

MCQs Skewness and Kurtosis

  • When a distribution is symmetrical and has one mode, the highest point on the curve is called the
  • If the moment Ratio $\beta_2=3$ then the distribution is
  • For a symmetrical distribution
  • The degree to which numerical data tend to spread out about an average value is called
  • In symmetrical distribution if $Q_1=4, Q_3=12$ then median is
  • The first three moments of a distribution about the mean $\overline{X}$ are 1, 4, and 0. The distribution is
  • The distribution is positively skewed if
  • In Symmetrical distribution $Q_3-Q_1=20$, Median = 15, $Q_3$ is equal to

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Introduction to R Language

Index Numbers An Introduction

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The index numbers are numbers that “measure a relative change in a variable or an average relative change in a group of related variables concerning a base”. An index number indicates the level of certain phenomena at some given period in comparison with the level of the same phenomena at some reference period. The index numbers are usually constructed for economic variables such as price, quantity, wage, unemployment, investment, cost of living, etc.

Index numbers are free from units of measurement because they show relative changes. For ease of understanding, index numbers are expressed in percentages. To construct an index number at least two periods are required and a period that is economically stable and has no major crisis caused by wars, diseases, strikes, food shortage, etc. known as the normal period is selected as a base. Index numbers of wholesale prices and consumer prices, etc. are published by the Federal Bureau of Statistics and State Bank of Pakistan.

Uses/ Need of Index Numbers

There are many uses for index numbers but the most important are:

  • Many economic plans and Government policies depend on index numbers, for example, to control rising prices of government imports from other countries or give subsidies (financial support) to the manufacturer.
  • The Price index number is used to know the purchasing ability of money at different periods and places.
  • The quantity index number is used to know the changes in the quantities produced, consumed, sold, purchased, imported or exported, etc.
  • Consumer price index numbers are used to know people’s standards of living and the goods and services used by them.
  • Index numbers are used to forecast future economic trends
  • Cyclical (long-term movements, which are in the form of oscillation) and seasonal (short-term movements, which are linked with the seasons or movements that repeat themselves within a fixed period) movements are measured by index number.
Index Numbers

Shortcomings of Index Number

Index numbers can not be used freely due to the following shortcomings:

  • An improper base period gives misleading results. Base periods must be free from all types of crises caused by wars, diseases, strikes, food shortages, etc. If such a period is not available then the average of some or all the periods is selected as the base.
  • Selection of favorite commodities is difficult because the use of services and commodities by individuals varies with the locality of people, social customs, standard of living, occupation, ideas of saving, courage of investment, and sources of income, etc.
  • The quality of a product cannot be observed at each point, that is, ball-to-ball commentary is difficult. For example, if we want to view the quality of cloth at each thread before purchasing it becomes impossible.
  • Index number gives a rough measure of relative changes because sampling error or error of measurement may occur at the stages of gathering data or the base period may be improper or the number of commodities may be less than required. According to Dr. Arriving Fisher, the accuracy of index numbers may be increased by increasing the number of commodities.
  • Different methods of index numbers usually give different results.
  • Prices vary from place to place according to the idea of profit of investors, expenditures on transportation, and awareness about the psychology of buyers, hence their collection is difficult.

Examples of Important Index Numbers:

  • Consumer Price Index (CPI): Tracks changes in the prices of goods and services purchased by consumers.
  • Producer Price Index (PPI): Measures the average change in prices received by domestic producers for their output.
  • Wholesale Price Index (WPI): Tracks the price changes of goods traded in wholesale markets.
  • Industrial Production Index (IPI): Measures the volume of physical production in the industrial sector.

In conclusion, index numbers are a powerful tool for summarizing complex economic information and identifying trends. They play a vital role in economic analysis, decision-making, and understanding changes in our world over time.

R Frequently Asked Questions

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