Steps of Research MCQ Quiz in मल्याळम - Objective Question with Answer for Steps of Research - സൗജന്യ PDF ഡൗൺലോഡ് ചെയ്യുക

Last updated on Mar 9, 2025

നേടുക Steps of Research ഉത്തരങ്ങളും വിശദമായ പരിഹാരങ്ങളുമുള്ള മൾട്ടിപ്പിൾ ചോയ്സ് ചോദ്യങ്ങൾ (MCQ ക്വിസ്). ഇവ സൗജന്യമായി ഡൗൺലോഡ് ചെയ്യുക Steps of Research MCQ ക്വിസ് പിഡിഎഫ്, ബാങ്കിംഗ്, എസ്എസ്‌സി, റെയിൽവേ, യുപിഎസ്‌സി, സ്റ്റേറ്റ് പിഎസ്‌സി തുടങ്ങിയ നിങ്ങളുടെ വരാനിരിക്കുന്ന പരീക്ഷകൾക്കായി തയ്യാറെടുക്കുക

Latest Steps of Research MCQ Objective Questions

Top Steps of Research MCQ Objective Questions

Steps of Research Question 1:

The tendency to subtly or unconsciously influence the behavior of the participants of a study, which obscures the true effect of the independent variable, is called

  1. Hawthorne Effect
  2. biosocial impact
  3. Experimenter Bias effect
  4. Participant bias

Answer (Detailed Solution Below)

Option 3 : Experimenter Bias effect

Steps of Research Question 1 Detailed Solution

Key Points 
  • Experimenter bias effect, also known as experimenter effect, occurs when the researchers' expectations, preferences, or other characteristics inadvertently influence the participants of a study, thus affecting the study's outcome.
  • This bias can lead to the subtle communication of expectations to participants in ways that might not be immediately obvious, such as through body language, tone of voice, or the manner in which questions are asked or experiments are conducted.
  • As a result, the behavior or responses of the participants may be influenced not solely by the manipulation of the independent variables intended by the study but also by the researchers' non-verbal cues or biases.
  • This can obscure or distort the true effect of the independent variable because the observed outcomes might reflect the experimenter’s expectations rather than the natural response to the experimental manipulation. For example, if a researcher expects a certain result from a specific group of participants, they might unconsciously interact with them in a way that encourages those results, even if the interaction seems neutral on the surface.
  • Experimenter bias is a significant concern in psychological and other types of research, as it threatens the internal validity of the experiment.
  • To mitigate this bias, researchers can implement double-blind procedures, where neither the participants nor the experimenters know the critical aspects of the experiment, such as who belongs to the control group and who belongs to the experimental group. This approach helps to ensure that expectations do not influence the results of the study.

Steps of Research Question 2:

Which of the following are remote data collection procedures?

(A) Third-party interview

(B) Pop-ups

(C) Database e-mail

(D) Instant messaging

(E) Panel discussions

Choose the correct answer from the options given below :

  1. (A), (B), (C) only 
  2. (B), (C), (D) only  
  3. (C), (D), (E) only 
  4. (A), (B), (E) only 

Answer (Detailed Solution Below)

Option 2 : (B), (C), (D) only  

Steps of Research Question 2 Detailed Solution

The correct answer is  (B), (C), (D) only.

Key Points 

Explanation: Remote data collection procedures refer to methods of collecting data from individuals or groups who are not physically present in a common location.

  • (B) Pop-ups: These are forms or ads that appear over the content of websites. In the context of data collection, they could be used for various purposes like capturing email addresses, understanding user preferences, collecting customer feedback, and more. As these interactions happen online, without face-to-face contact, pop-ups are considered a remote data collection process.

 

  • (C) Database E-mail: In the context of data collection, this could refer to strategies where information is gathered through emails. This can range from sending out surveys via email to simply analyzing user responses from their emails. As this collects data remotely without physical interactions, it is considered a remote data collection method.

 

  • (D) Instant Messaging: This could refer to several types of synchronous written online communication like Slack, WhatsApp, or Facebook Messenger. These can be used for conducting interviews, group discussions, or surveys where the participants can respond in real time but without any face-to-face interaction. This makes instant messaging a remote data collection method.

The other options, (A) Third party interview, and (E) Panel discussions are not typically considered remote data collection procedures as they require a physical presence in a common location.

(A) Third-party interview: This is a research method where someone other than the primary researcher conducts the interview.

  • This could be brought into the remote data collection category if the interview is carried out remotely via video conferencing or phone interviews. However, it can also be conducted face-to-face, which precludes it from being purely a remote data collection method.
  • Therefore, whether it belongs to remote data collection methods or not depends on the specific context in which it's conducted.

 

(E) Panel discussions: This refers to a discussion format where a group of people gathers to discuss a topic, often in front of an audience.

  • This can be conducted both face-to-face or remotely (like webinars or video conferences). However, it's not typically, from a traditional standpoint, considered remote as they often occur in person.
  • Because of this, it typically wouldn't fall into the category of a remote data collection method unless it is specified that it is conducted remotely.

 

Additional Information

There are several methods of data collection, which can be broadly categorized into two categories: primary data collection and secondary data collection. 

  1. Primary Data Collection:

    • Surveys: Surveys can be conducted through various mediums such as mail, phone, online, or in-person interviews. Surveys are a popular method of primary data collection as they allow researchers to gather large amounts of data from a diverse group of people.

    • Observations: Observational research involves observing and recording data systematically. It can be conducted in a natural setting or a controlled laboratory environment.

    • Experiments: Experiments are designed to test causal relationships between variables. In an experiment, researchers manipulate one or more independent variables and observe the effect on the dependent variable.

    • Focus groups: Focus groups are moderated group discussions designed to gather information about a specific topic. They are often used to collect qualitative data and to gain a deeper understanding of attitudes and behaviors.

  2. Secondary Data Collection:

    • Literature review: This method involves collecting data from existing sources such as journal articles, books, and reports. The data collected from this method is often used to build a theoretical foundation or to provide background information.

    • Database: A database is a collection of data organized in a specific way. Data can be collected from databases maintained by government agencies, private organizations, or individuals.

    • Archives: Archives refer to collections of historical records and documents that can be used to gather data. These records can be stored in physical archives or in digital archives.

 

Steps of Research Question 3:

When a researcher rejects a true 'Null Hypothesis' (H0) in his/her study and accepts the 'Alternate Hypothesis' (H1), what type of error is likely?

  1. Type I error
  2. Type II error
  3. Both Type I and Type II error
  4. Neither Type I nor Type II error

Answer (Detailed Solution Below)

Option 1 : Type I error

Steps of Research Question 3 Detailed Solution

Hypothesis testing use sample data to make inference about the properties of a population study.

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  • Samples used are typically a minute proportion of the population thereby leading to misrepresenting the population to cause the hypothesis test to make an error.

There are two types of errors in hypothesis testing. They are Type 1 and Type 2 errors. Both relate to an incorrect conclusion about the null hypothesis.

1. Type I error
  • When the null hypothesis is true and you reject it, you make a type I error.
  • The probability of making a type I error is α, which is the level of significance you set for your hypothesis test.
  • An α of 0.05 indicates that you are willing to accept a 5% chance that you are wrong when you reject the null hypothesis.
  • To lower this risk, you must use a lower value for α.
  • However, using a lower value for alpha means that you will be less likely to detect a true difference if one really exists.
  • When the null hypothesis is false and you fail to reject it, you make a type II error.
  • The probability of making a type II error is β, which depends on the power of the test.
  • You can decrease your risk of committing a type II error by ensuring your test has enough power.
  • You can do this by ensuring your sample size is large enough to detect a practical difference when one truly exists.

The probability of rejecting the null hypothesis when it is false is equal to 1–β. This value is the power of the test.

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2. Type II error

 

Truth about the population

Decision based on sample

H0 is true

H0 is false

Fail to reject H0

Correct Decision (probability = 1 - α)

Type II Error - fail to reject H0 when it is false (probability = β)

Reject H0

Type I Error - rejecting H0 when it is true (probability = α)

Correct Decision (probability = 1 - β)

Therefore option 1 is the correct answer.

Steps of Research Question 4:

Given below are two statements:

Statement I: A Type-I error occurs when the null hypothesis is true and you reject it.

Statement II: A Type-II error occurs when you fail to reject a false Null hypothesis. 

In the light of the above statements choose the correct answer from the options given below:

  1. Both Statement I and Statement II are true
  2. Both Statement I and Statement II are false 
  3. Statement I is true but Statement II is false
  4. Statement I is false but Statement II is true

Answer (Detailed Solution Below)

Option 1 : Both Statement I and Statement II are true

Steps of Research Question 4 Detailed Solution

  • The term hypothesis means prediction or tentative statement.
  • We form a hypothesis before doing research.
  • A hypothesis is tested on various parameters in order to know the relation between the variables.
  • A good hypothesis should be clear and precise.
  • It should be capable of being tested. It must be stated in simple terms.
  • It makes the research more meaningful by giving direction to the research.
  • There are two types of hypothesis one is the Null Hypothesis and the other is the Alternate hypothesis.

Key Points

Null Hypothesis (H0):

  • Null hypothesis means there is no difference between the two situations.
  • It is denoted by the symbol  (Ho ).
  • Null Hypothesis statements are not proved by the researcher.
  • It is assumed that there is no observed effect between two null hypothesis statements.
  • Example - In an analysis, if we compare Method A and Method B, we proceed with the assumption that both methods are equally good then this assumption is termed as the Null Hypothesis.

Alternate Hypothesis (H1):

  • The alternate hypothesis is also known as a substantive research hypothesis.
  • It is denoted by the symbol (H1) or (Ha).
  • It means a statement in which there is a statistically significant difference between two measured phenomena.
  • Alternate Hypothesis statements are proved by the researcher.
  • It is assumed that there is some observed effect between two alternate hypothesis statements.
  • Example - In an analysis, if we found that boys are more good in math than girls. This tentative statement is known as an Alternate hypothesis as there exists a difference between the two variables.

Important PointsTypes of Error - There are two types of error i.e. Type I error and Type II error

Type I Error
  • If the Null hypothesis is correct but still rejected by the researcher it is called a Type I error.
  • It is denoted by the Greek letter alpha (a). Also called an alpha error.
  • It is an incorrect rejection of a true Null hypothesis that's why it is a false positive.
Type II error
  • If the Null hypothesis is wrong but still accepted by the researcher it is called a Type II error.
  • It is denoted by the Greek letter beta (B). Also called a beta error.
  • It is an incorrect acceptance of a false Null hypothesis that's why it is a false negative.

Thus, Both Statement I and Statement II are true.

Steps of Research Question 5:

Which of the following is not an example of probability sampling?

  1. Stratified sampling
  2. Snowballl sampling
  3. Cluster sampling
  4. Systematic sampling

Answer (Detailed Solution Below)

Option 2 : Snowballl sampling

Steps of Research Question 5 Detailed Solution

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Probability sampling:

  • Probability sampling methods are those that clearly specify the probability or likelihood of inclusion of each element or individual in the sample.
  • These are free of bias in selecting sample units.
  • They help in the estimation of sampling errors and evaluate sample results in terms of their precision, accuracy, and efficiency, and hence, the conclusions reached from such samples are worth generalization and comparable to the similar populations to which they belong.
  • Major probability sampling methods are simple random sampling, stratified random sampling, and Cluster sampling, and Systematic sampling.


Hence, only the snowball sampling method is not a probability sampling method.

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Snowball Sampling:

  • It is also called network or chain referral sampling.
  • To start with, the researcher identifies a small number of respondents having a set of characteristics of interest to the researcher.
  • After collecting the required data from those respondents, the same respondents are asked to identify others having the same characteristics set.
  • E.g., collecting data from drug addicts, rape victims, etc.

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Random/Probability Sampling: In this type, each element in the population has an equal and independent chance of selection in the sample.

  1. Stratified Random Sampling: It combines randomization with stratification. Here, the population is divided into strata, the population within each stratum is homogeneous with respect to the characteristic based on which it is being stratified and such characteristics must be identifiable in the study population (e.g. age, income, sex, etc.).
  1. Systematic sampling is a statistical method that researchers use to zero down on the desired population they want to research. Researchers calculate the sampling interval by dividing the entire population size by the desired sample size.
  2. Cluster Sampling: It is based on the ability of the researcher to divide the sampling population into groups, called clusters and then to select elements within each cluster, using the simple random sampling technique. It is appropriate when the population is large.

Steps of Research Question 6:

Which of the following sampling techniques in research imply randomization and equal probability of drawing the units?

A. Quota sampling

B. Snowball sampling

C. Stratified sampling

D. Dimensional sampling

E. Cluster sampling

Choose the correct answer from the option given below:

  1. A and B only
  2. B and C only
  3. C and E only
  4. D and E only

Answer (Detailed Solution Below)

Option 3 : C and E only

Steps of Research Question 6 Detailed Solution

According to Croach and Housden, a sample is a limited number taken from a large group for testing and analysis, on the assumption that the sample can be taken as representative for the whole group.

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There are broadly two types of sampling: i) Probability sampling ii) Non-probability sampling

A) Probability Sampling

  • Probability sampling is defined as a sampling technique in which the researcher chooses samples from a larger population using a method based on the theory of probability.
  • For a participant to be considered as a probability sample, he/she must be selected using a random selection.
  •  The most critical requirement of probability sampling is that everyone in your population has a known and equal chance of getting selected

Probability methods include simple random sampling, systematic sampling, cluster sampling, and stratified sampling.

1. Stratified SamplingStratified sampling is a type of sampling method in which the total population is divided into smaller groups or strata to complete the sampling process. The strata are formed based on some common characteristics in the population data. After dividing the population into strata, the researcher randomly selects the sample proportionally.

2. Cluster SamplingCluster sampling is a probability sampling technique where researchers divide the population into multiple groups (clusters) for research. Researchers then select random groups with a simple random or systematic random sampling technique for data collection and data analysis.

Thus, option 3 is the correct answer.

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B) Non-Probability Sampling:

  • Such a sample is also called a purposive sample. 
  • Non-probability sampling is defined as a sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection. 

There are many types of non-probability samples, including snowball sampling, convenience, purposive/ judgment, quota sampling, dimensional sampling, etc.

1. Quota Sampling: In quota sampling, the population is categorized into several strata which consist of the expected size, and the samples are considered to be important for the population they represent. The advantages of a quota sample are that it involves a short time duration, is less costly, and gives moderate representation to a heterogeneous population. 

2. Snowball Sampling: This is one of the important types of non-probability sampling. In snowball sampling, the investigator encourages the respondents to give the names of other acquaintances and it continues growing in size and chains until the research purpose is achieved. It is also, therefore, known as networking, chain, or referred sampling method. It is very useful in the study of networking and is less costly.

3. Dimensional Sampling: Dimensional sampling is an extension of quota sampling. The researcher takes into account several characteristics e.g. gender, age, income, residence, and education. The researcher must ensure that there is at least one person in the study representing each of the chosen characteristics.

Steps of Research Question 7:

Hypothesis, that is alternative to null hypothesis, is represented as

  1. H0
  2. H1
  3. Halt
  4. H≠0

Answer (Detailed Solution Below)

Option 2 : H1

Steps of Research Question 7 Detailed Solution

The correct response is H1.

Key Points

  • A hypothesis is a statement or explanation that is put forward as a possible explanation for a phenomenon.
  • The alternative hypothesis can take different forms, including a two-tailed alternative hypothesis (i.e., the mean difference could be either positive or negative) or a one-tailed alternative hypothesis (i.e., the mean difference could only be in one direction).
  • In a hypothesis test, the null hypothesis is typically rejected if the evidence supports the alternative hypothesis. The alternative hypothesis provides the basis for making inferences about the population based on the sample data.
  • For example, if the null hypothesis is "there is no difference in mean height between Group A and Group B," the alternative hypothesis might be "there is a difference in mean height between Group A and Group B."

 

Therefore, Hypothesis, that is alternative to null hypothesis, is represented as H1.

Important Points

  • In scientific research, a hypothesis is a testable prediction about the relationship between variables.
  • It provides a basis for conducting further research to test its validity.
  • A hypothesis is usually based on prior knowledge, observations, and theories, and is designed to be falsifiable, meaning it can be tested and potentially disproved. 
  • The process of testing a hypothesis involves collecting data, analyzing the data, and determining whether the evidence supports or rejects the hypothesis.
  • The alternative hypothesis is a statement about the population parameter that is opposite or different from the null hypothesis.
  • The alternative hypothesis is represented as H1 or Ha, where H1 represents the hypothesis of interest and Ha represents the alternative hypothesis.
  • The alternative hypothesis is a statement of what the researcher believes is true and what they are testing in a study.
  • The alternative hypothesis typically reflects the research question and the direction of the relationship between the variables being studied.

 

Additional Information quesImage2466

Steps of Research Question 8:

To perform t-test which of the following softwares can be utilized? 

(A) MS Excel

(B) Unix

(C) SPSS

(D) MS Equations

Choose the most appropriate answer from the options given below : 

  1. (A) and (B) only 
  2. (B), (C) and (D) only 
  3. (A) and (C) only 
  4. (A), (C) and (D) only 

Answer (Detailed Solution Below)

Option 3 : (A) and (C) only 

Steps of Research Question 8 Detailed Solution

The answer is  (A) and (C) only.Key Points 

T-test is a statistical method used to determine if there is a significant difference between the means of two groups

 T-Test

  • The t-test tells you how significant the differences between groups are; In other words it lets you know if those differences (measured in means) could have happened by chance.
  •  The t-test is one of many tests used for the purpose of hypothesis testing in statistics.
  • There are two types of statistical inference: parametric and nonparametric methods.
  • Parametric methods refer to a statistical technique in which one defines the probability distribution of probability variables and makes inferences about the parameters of the distribution.
  • In cases in which the probability distribution cannot be defined, nonparametric methods are employed.
  • T-tests are a type of parametric method; they can be used when the samples satisfy the conditions of normality, equal variance, and independence.
  • It is a two-tailed test

Important Points

  • (A) MS Excel: Microsoft Excel provides basic statistical analysis tools, including t-tests. This means that users can perform t-tests using Excel's built-in functions and formulas.

  • (C) SPSS: SPSS (Statistical Package for the Social Sciences) is a software package that provides advanced statistical analysis tools, including t-tests. This means that users can perform t-tests using SPSS's advanced features and functions.

Both MS Excel and SPSS can be utilized to perform t-tests, which makes options 3) (A) and (C) only the correct answer.Key Points 

Here is a table explaining the use and definition of the software programs mentioned:

Software Program Use Definition
MS Excel Basic statistical analysis, data organization, and presentation A spreadsheet program that provides basic statistical analysis tools, including t-tests, as well as other functions for organizing, analyzing, and presenting data.
Unix Operating system, network management, and software development A computer operating system that provides a stable, multi-user, and multi-tasking environment. Unix is not typically used for performing t-tests, but it is widely used for network management and software development.
SPSS Advanced statistical analysis A software package that provides advanced statistical analysis tools, including t-tests, as well as other functions for organizing, analyzing, and presenting data. SPSS is widely used in social science research, market research, and other fields that require sophisticated statistical analysis.
MS Equations Mathematical equation editing and formatting A software package that provides basic mathematical equation editing and formatting capabilities. MS Equations is not typically used for performing t-tests or other statistical analyses.

Steps of Research Question 9:

Of type I and type II error, one which traditionally regarded as more serious is

  1. Type I
  2. Type II
  3. They are equally serious
  4. Neither is serious

Answer (Detailed Solution Below)

Option 1 : Type I

Steps of Research Question 9 Detailed Solution

The correct answer is - Type I.

Key Points
  • A Type I error means rejecting the null hypothesis when it’s true.
  • It means concluding that results are statistically significant when, in reality, they came about purely by chance or because of unrelated factors.
  • Type II error means not rejecting the null hypothesis when it’s false.
  • It means failing to conclude there was an effect when there actually was.
  • A Type I error means mistakenly going against the main statistical assumption of a null hypothesis.
  • This may lead to new policies, practices, or treatments that are inadequate or a waste of resources.
  • In contrast, a Type II error means failing to reject a null hypothesis. It may only result in missed opportunities to innovate, but these can also have important practical consequences.
  H0 is true H0 is false
Do not reject H0 Correct decision Type II error
Reject H0 Type I error Correct decision

Therefore, for statisticians, a Type I error is traditionally regarded as more serious 

Steps of Research Question 10:

Which of the following statements is true in the context of the testing of a hypothesis?

  1. It is only the alternative hypothesis, that can be tested.
  2. It is only the null hypothesis, that can be tested.
  3. Both, the alternative and the null hypotheses can be tested.
  4. Both, the alternative and the null hypotheses cannot be tested.

Answer (Detailed Solution Below)

Option 2 : It is only the null hypothesis, that can be tested.

Steps of Research Question 10 Detailed Solution

Hypothesis Testing

  • In hypothesis testing, an analyst tests a statistical sample, with the goal of providing evidence on the plausibility of the null hypothesis.
  • The null hypothesis is usually a hypothesis of equality between population parameters; e.g., a null hypothesis may state that the population mean return is equal to zero.
  • The alternative hypothesis is effectively the opposite of a null hypothesis; e.g., the population mean return is not equal to zero.
  • Thus, they are mutually exclusive, and only one can be true.
  • However, one of the two hypotheses will always be true.

Four Steps of Hypothesis Testing

All hypotheses are tested using a four-step process:

  1. The first step is for the analyst to state the two hypotheses so that only one can be right.
  2. The next step is to formulate an analysis plan, which outlines how the data will be evaluated.
  3. The third step is to carry out the plan and physically analyze the sample data.
  4. The fourth and final step is to analyze the results and either reject the null hypothesis, or state that the null hypothesis is plausible, given the data.

Therefore, in the context of the testing of a hypothesis, it is only the null hypothesis, that can be tested.

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