Research MCQ Quiz in मराठी - Objective Question with Answer for Research - मोफत PDF डाउनलोड करा

The correct answer is 'A - IV, B - I, C - II, D - III'

Key Points

• Classical Conditioning:
  • Defined as a form of associative learning where a neutral stimulus becomes associated with a meaningful stimulus and acquires the ability to elicit a similar response.
  • Example: Pavlov's dogs, where the sound of a bell (neutral stimulus) was associated with food (meaningful stimulus) to eventually produce salivation (response).
• Operant Conditioning:
  • A form of learning in which the consequences of behavior produce changes in the probability that the behavior will occur.
  • Example: B.F. Skinner's experiments with pigeons and rats where behaviors were shaped by rewards and punishments.
• Reinforcement:
  • A consequence that increases the probability that a behavior will occur.
  • Can be positive (adding a desirable stimulus) or negative (removing an undesirable stimulus).
• Punishment:
  • A consequence that decreases the probability that a behavior will occur.
  • Can be positive (adding an undesirable stimulus) or negative (removing a desirable stimulus).

Additional Information

• Option 2:
  • Incorrect as it mismatches the concepts with their descriptions. For example, Reinforcement is not associated with Classical Conditioning.
• Option 3:
  • Incorrect as it incorrectly matches the descriptions. For example, Operant Conditioning is not about decreasing the probability of behavior.
• Option 4:
  • Incorrect as it incorrectly places Classical Conditioning and Operant Conditioning descriptions.

All units available in population must be known

Key Points

• Simple Random Sampling:
  • Simple random sampling is a technique where each unit of the population has an equal chance of being selected.
  • This method ensures that the sample is representative of the population, thereby minimizing bias.
  • To achieve this, it is essential that all units in the population are known and accessible.

Additional Information

• It is not essential to know all units available in population:
  • This statement is incorrect because, without knowing all units, it is impossible to ensure that each unit has an equal chance of being selected.
• All units must be classified in different strata before sampling:
  • This refers to stratified sampling, not simple random sampling. In stratified sampling, the population is divided into strata, and samples are drawn from each stratum.
• Choice of investigator while sample selection is considered:
  • This is incorrect as it introduces bias. Simple random sampling requires that the selection process be free from any investigator influence.

The correct answer is 'It is not necessary that given units may be orderly ranked.'

Key Points

• Arithmetic Mean:
  • The arithmetic mean is a measure of central tendency, commonly known as the average.
  • It is calculated by summing all the values in a data set and then dividing by the number of values.
• Why Option 2 is Correct:
  • For the calculation of arithmetic mean, it is necessary that the data should be quantitative and can be orderly ranked.
  • Option 2 states that it is not necessary for the units to be orderly ranked, which is incorrect as ordered data is essential for accurate mean calculation.
• Other Options:
  • Option 1: Its calculation is easy.
    • This is correct as the arithmetic mean is relatively simple to calculate.
  • Option 3: It takes into consideration all the scores in distribution.
    • This is also correct because the mean involves all data points in its calculation.
  • Option 4: Mean is useful in calculating ratio.
    • This is true as the mean can be used in further statistical analysis, including ratio calculations.

Additional Information

• Importance of Arithmetic Mean:
  • It is widely used in various fields like economics, finance, and social sciences.
  • The arithmetic mean provides a single value representing the center of the data distribution, making it easier to compare different data sets.
• Limitations of Arithmetic Mean:
  • It can be affected by extreme values (outliers), which can distort the mean.
  • It is not suitable for skewed distributions as it may not accurately represent the central tendency.

Match List - I with List - II

Key Points

• Research:
  • Researcher's proposition about some social fact without reference to its attributes.
  • This involves forming a hypothesis based on preliminary observations or assumptions where sufficient information may not be available.
• Working Hypothesis:
  • Preliminary assumption of researcher about topic when sufficient information is not available.
  • Often used as a starting point for further investigation and research.
• Alternative Hypothesis:
  • Set of two hypotheses which states opposite to null hypothesis.
  • In hypothesis testing, the alternative hypothesis is what you might believe to be true or hope to prove true.
• Scientific Hypothesis:
  • Statement based on sufficient theoretical and empirical data.
  • This type of hypothesis is well-founded and often tested through scientific methods.

Additional Information

• Option Analysis:
  • Option 1: A - I, B - II, C - III, D - IV
    • Incorrect because it does not correctly match the definitions with the types of hypotheses.
  • Option 2: A - III, B - IV, C - I, D - II
    • Correct as it accurately matches the definitions to the respective types of hypotheses.
  • Option 3: A - II, B - IV, C - I, D - III
    • Incorrect because it misplaces the definitions.
  • Option 4: A - IV, B - II, C - III, D - I
    • Incorrect as it mismatches the definitions and types.

The correct answer is 'A is true but R is false'

Key Points

• Assertion A:
  • Repeated measures ANOVA is a statistical technique used to determine the significance of mean differences when the same subjects are measured multiple times.
  • It is particularly useful in experiments where measurements are taken on the same subjects under different conditions or over different time points.
• Reason R:
  • The statement that Repeated measures ANOVA is not used in testing designs where subjects are measured before, during, and after treatment is incorrect.
  • In fact, Repeated measures ANOVA is specifically designed for such scenarios to analyze the changes over time or conditions.

The correct answer is 'C, D, B, A, E'

Key Points

• Identifying the constructs:
  • This is the first step in constructing a questionnaire. Constructs are the abstract ideas or themes that the questionnaire aims to measure. Identifying these helps in formulating relevant questions.
• Deciding the format of questions:
  • Once the constructs are identified, the next step is to decide the format of the questions. This includes whether the questions will be open-ended, closed-ended, multiple-choice, etc.
• Constructing questions:
  • After deciding the format, the actual construction of questions begins. This involves writing questions that are clear, concise, and relevant to the constructs.
• Ordering and sequencing of questions:
  • Once the questions are constructed, they need to be ordered and sequenced logically. This ensures a smooth flow and makes the questionnaire easier to understand and complete.
• Writing instructions for respondents:
  • The final step is to write clear instructions for respondents. This includes explaining how to answer the questions and any other relevant information needed to complete the questionnaire.

The correct answer is 'B, D, A, C, E'

Key Points

• Sequential steps of constructing a Likert summated rating scale:
  • Construction of items (B): The first step involves developing a pool of items that are relevant to the construct being measured. These items should be clear, concise, and capable of eliciting a range of responses.
  • Evaluation of items by experts (D): Once the items are constructed, they are evaluated by experts in the field to ensure content validity. Experts review the items for clarity, relevance, and potential biases.
  • Trail test on small sample (A): The next step is to conduct a trial test on a small sample of respondents. This helps to identify any issues with the items and allows for preliminary analysis.
  • Item analysis (C): After the trial test, item analysis is performed to determine the discriminatory power of each item. Items that do not perform well are revised or discarded.
  • Reliability estimation (E): Finally, the reliability of the scale is estimated using statistical methods such as Cronbach's alpha. This ensures that the scale consistently measures the construct of interest.

The correct answer is 'A - III, B - IV, C - I, D - II'

Key Points

• Mixed methods research:
  • An approach to inquiry that combines qualitative and quantitative research forms (List I: C, List II: I).
  • This approach allows for a more comprehensive analysis by leveraging the strengths of both qualitative and quantitative data.
• Mixed methods notation:
  • Shorthand labels conveying important aspects of mixed methods research (List I: A, List II: III).
  • These notations help in quickly identifying the structure and components of the mixed methods approach used in a study.
• Mixed methods purpose statement:
  • Overall intent covering both qualitative and quantitative strands (List I: B, List II: IV).
  • This statement provides a clear rationale for why both qualitative and quantitative approaches are being used in the research.
• Mixed method research question:
  • Special question directly addressing the mix of qualitative and quantitative strands (List I: D, List II: II).
  • These questions are designed to integrate both forms of data to answer complex research problems.

The correct answer is 'A, C and D only'

Key Points

• Power of a test:
  • The power of a test is the probability that the test will correctly reject a false null hypothesis. This means that the test is able to detect an actual effect when there is one.
  • The power of a test is influenced by several factors including the sample size, significance level, and the true effect size.
• Key Points related to the given options:
  • Option A: Ability to detect the real effect in a population based on a sample taken from the population. This is correct because it aligns with the definition of the power of a test.
  • Option C: Increased when sample size increases. This is correct because a larger sample size generally provides more information and increases the ability to detect a true effect.
  • Option D: Probability of correctly rejecting the null hypothesis when it is false. This is the correct statistical definition of the power of a test.

The correct answer is 'Normal distribution'.

Key Points

• Normal distribution:
  • A normal distribution is a continuous probability distribution that is symmetrical around its mean.
  • The histogram of a normal distribution forms a bell-shaped curve that peaks at the mean, which is also the median and mode of the distribution.
  • This distribution is significant in statistics because many variables are naturally distributed normally, and it has important properties that facilitate statistical inference.
  • In a normal distribution, the data is evenly distributed on both sides of the peak, creating a balanced, bell-shaped curve.

Additional Information

• Positively skewed distribution:
  • In a positively skewed distribution, the tail on the right side of the histogram is longer or fatter than the left side.Most of the data points are concentrated on the left, and the mean is greater than the median.
• Negatively skewed distribution:
  • In a negatively skewed distribution, the tail on the left side of the histogram is longer or fatter than the right side.
  • Most of the data points are concentrated on the right, and the mean is less than the median.
• Distribution in which the mean, mode, and median do not coincide:
  • This describes any distribution where the mean, median, and mode are not the same, which is typical of skewed distributions.
  • In contrast, in a normal distribution, these three measures of central tendency coincide.