# Data Analysis And Reporting Quiz! Trivia

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Are you in the field of Data analysis and reporting? There are different ways that data is collected for research methods and the reporting methods also vary. It is important to ensure that the information gathered is reliable and helps in the intended research. How do you gauge the significance of the data you have? This quiz will help you find out. Take it up and test your data analysis skills. All the best!

• 1.

### This value indicates the probability that the null hypothesis is true and so it follows that a researcher would want a very small probability value in order to be able to claim that the test result is statistically significant.

• A.

Level of Significance

• B.

Probability Value

A. Level of Significance
Explanation
The level of significance is a value that determines the threshold for rejecting the null hypothesis in a statistical test. It represents the maximum probability that the researcher is willing to accept for making a Type I error (incorrectly rejecting the null hypothesis). In other words, it indicates the probability of obtaining the observed test result if the null hypothesis is true. Therefore, a researcher would want a very small level of significance (typically 0.05 or 0.01) to be able to claim that the test result is statistically significant and reject the null hypothesis.

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• 2.

### The 5% level of significance can also be written as........ (where p = the probability of the result occurring if the null hypothesis were true)

• A.

P = .5

• B.

p = .05

B. p = .05
Explanation
The 5% level of significance represents the threshold at which we reject the null hypothesis in hypothesis testing. It indicates that if the probability of the result occurring, assuming the null hypothesis is true, is less than or equal to 5%, we reject the null hypothesis. In this case, p = .05 represents the 5% level of significance, indicating that the result is statistically significant if the probability of occurrence under the null hypothesis is 5% or less.

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• 3.

### When the 5% significance level is achieved in quantitative research, providing that the study has been carefully designed and executed, a more likely explanation is that the result is due to the effects of the manipulated independent variable.

• A.

The null hypothesis is, therefore, rejected.

• B.

The null hypothesis is, therefore, retained

A. The null hypothesis is, therefore, rejected.
Explanation
When the 5% significance level is achieved in quantitative research, it means that the probability of obtaining the observed result by chance is less than 5%. This suggests that the result is unlikely to be due to random variation and is more likely to be a result of the effects of the manipulated independent variable. Therefore, the null hypothesis, which assumes that there is no effect of the independent variable, is rejected.

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• 4.

### If the 5% level of significance or less is achieved (p < .05) this means that the probability of observing that particular result, if the null hypothesis is true, is.....

• A.

1 in 5 (or 20%) or less.

• B.

1 in 20 (or 5%) or less.

B. 1 in 20 (or 5%) or less.
Explanation
If the 5% level of significance or less is achieved (p < .05), it means that the probability of observing that particular result, if the null hypothesis is true, is 1 in 20 (or 5%) or less. This indicates that the likelihood of obtaining the observed result by chance under the assumption that the null hypothesis is true is very low, providing evidence to reject the null hypothesis in favor of the alternative hypothesis.

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• 5.

### A Type 1 error occurs when a null hypothesis......

• A.

Is rejected when it should have not been.

• B.

Is retained when it should not have been.

A. Is rejected when it should have not been.
Explanation
A Type 1 error occurs when a null hypothesis is rejected when it should have not been. This means that the statistical test incorrectly concludes that there is a significant effect or relationship when in reality there is not. It is a false positive result, indicating that there is evidence for something that is not actually true.

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• 6.

### A Type 2 error occurs when a null hypothesis......

• A.

Is retained when it should not have been.

• B.

Is rejected when it should have not been.

A. Is retained when it should not have been.
Explanation
A Type 2 error occurs when a null hypothesis is retained when it should not have been. This means that the null hypothesis is accepted or not rejected, even though it should have been rejected based on the evidence or data. In other words, it is a failure to reject a false null hypothesis, leading to a conclusion that there is no effect or relationship when there actually is one.

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• 7.

### In a statistical context, the term ‘population’ refers to a

• A.

Complete data set rather than to a sample (a subgroup) of the population.

• B.

Sample (a subgroup) of the population rather than to a complete data set

A. Complete data set rather than to a sample (a subgroup) of the population.
Explanation
In statistics, the term "population" refers to the complete data set that includes all individuals or elements being studied. It encompasses every member of the group under investigation, providing a comprehensive view of the entire population. On the other hand, a sample is a subset or subgroup of the population that is selected for analysis. The sample is used to make inferences and draw conclusions about the population as a whole. Therefore, the correct answer is that "population" refers to a complete data set rather than a sample.

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• 8.

### The type of research design - The test you use will depend on whether the design of your experiment was independent or related (matched pairs or repeated measures) - Is a factor affecting the

• A.

Choice of Statistical Test

• B.

Choice of Sampling Method

A. Choice of Statistical Test
Explanation
The type of research design, whether it is independent or related (matched pairs or repeated measures), affects the choice of statistical test. Different research designs require different statistical tests to analyze the data accurately. For example, if the design is independent, where different groups are compared, a t-test or ANOVA may be appropriate. On the other hand, if the design is related, where the same group is measured multiple times, a paired t-test or repeated measures ANOVA may be more suitable. Therefore, the choice of statistical test depends on the research design to ensure the correct analysis of the data.

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• 9.

### The type of data - The data will be measured on either a nominal, ordinal or ratio scale - Is a factor affecting the

• A.

Choice of Sampling Method

• B.

Choice of Statistical Test

B. Choice of Statistical Test
Explanation
The type of data, whether it is measured on a nominal, ordinal, or ratio scale, affects the choice of statistical test. Different statistical tests are designed to analyze different types of data. For example, if the data is nominal, a chi-square test may be appropriate, while if the data is ordinal, a Mann-Whitney U test may be more suitable. The choice of statistical test depends on the nature of the data and the research question being investigated.

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• 10.

### Data on this most basic scale of measurement simply involve distinguishing between different and mutually exclusive categories of a variable e.g. smokers/non-smokers.

• A.

Nominal Data

• B.

Ordinal Data

A. Nominal Data
Explanation
The given answer is Nominal Data because it states that data on this scale involve distinguishing between different and mutually exclusive categories of a variable. Nominal data is the most basic scale of measurement where categories are used to label and classify data, without any specific order or ranking. In this case, the categories are smokers and non-smokers, which are distinct and exclusive groups. Therefore, the answer accurately describes the characteristics of Nominal Data.

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• 11.

### Can be organised into categories but these categories can also be placed in a logical order based on their meaning e.g. categories used to measure social class.

• A.

Interval Data

• B.

Ordinal Data

B. Ordinal Data
Explanation
Ordinal data refers to data that can be organized into categories and ranked in a specific order, but the differences between the categories are not necessarily equal. In this context, the statement suggests that the categories used to measure social class can be organized into groups, but they can also be arranged in a logical order based on their meaning. This implies that the categories have a specific hierarchy or ranking, indicating that the data being referred to is ordinal data.

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• 12.

### Units of measurement that can be placed in a logical order and the intervals between adjacent units on the scale are equal because they are based on some standard unit of measurement e.g. the Celsius temperature scale.

• A.

Nominal Data

• B.

Interval Data

B. Interval Data
Explanation
Interval data is the correct answer because it refers to a type of measurement scale where the units of measurement can be arranged in a logical order and the intervals between adjacent units are equal. This is possible because interval data is based on a standard unit of measurement, such as the Celsius temperature scale. Nominal data, on the other hand, does not have a logical order or equal intervals between units.

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• 13.

### Measurements on a scale that has equal intervals and also a genuine zero-point e.g. height in centimeters or weight in kilograms.

• A.

Ratio Data

• B.

Interval Data

A. Ratio Data
Explanation
Ratio data refers to measurements that have equal intervals and a genuine zero-point. In this case, height in centimeters and weight in kilograms are examples of ratio data because they have equal intervals (each unit of measurement is the same size) and a genuine zero-point (zero centimeters or zero kilograms represents the absence of height or weight).

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• 14.

### A test of statistical significance does not make any assumptions about the parameters (limits) underlying the distribution of the quantitative data.

• A.

Non-Parametric Test

• B.

Parametric Test

A. Non-Parametric Test
Explanation
A non-parametric test is used when the underlying distribution of the quantitative data is unknown or does not follow a specific distribution. It does not make any assumptions about the parameters or limits of the distribution. In contrast, a parametric test assumes that the data follows a specific distribution and makes assumptions about the parameters of that distribution. Therefore, the given statement aligns with the characteristics of a non-parametric test.

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• 15.

### Is a test of difference that is suitable for comparing data gathered from two groups in an experiment using an independent group design. It can be used with ordinal data.

• A.

The Mann-Whitney U Test

• B.

The Wilcoxon Test

A. The Mann-Whitney U Test
Explanation
The Mann-Whitney U Test is a statistical test that is appropriate for comparing data collected from two groups in an experiment using an independent group design. It can be used when the data is in ordinal form, meaning that it can be ranked but not necessarily measured on a continuous scale. This test is useful in situations where the assumptions of parametric tests, such as the t-test, are not met. The Mann-Whitney U Test calculates the probability that the observed differences between the two groups are due to chance, and provides a p-value to determine if the groups are significantly different from each other.

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• 16.

### If this value is equal to or less than the critical value for a given level of significance, the null hypothesis can be rejected - This applies to

• A.

The Wilcoxon Test

• B.

The Mann-Whitney U Test

B. The Mann-Whitney U Test
Explanation
The Mann-Whitney U Test is a nonparametric test used to compare two independent groups. It is used when the data does not meet the assumptions of a parametric test. In this case, if the calculated test statistic (U) is equal to or less than the critical value for a given level of significance, it means that the observed difference between the two groups is statistically significant. Therefore, the null hypothesis, which states that there is no difference between the groups, can be rejected.

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• 17.

### A test of difference, suitable for use with data gathered from an experiment, using a related (matched pairs or repeated measures) design. It can be used on ordinal data.

• A.

The Chi Squared Test

• B.

The Wilcoxon Test

B. The Wilcoxon Test
Explanation
The Wilcoxon Test is a suitable test for analyzing data gathered from an experiment that uses a related design, such as matched pairs or repeated measures. It is particularly useful when the data is ordinal, meaning it can be ranked or ordered. The test is used to determine if there is a significant difference between two related groups or conditions. It is a non-parametric test, meaning it does not assume a specific distribution for the data. Instead, it compares the ranks of the observations to assess the likelihood of obtaining the observed differences by chance.

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• 18.

### If the observed value of T is equal to, or less than, the critical value for a given level of significance, the null hypothesis can be rejected - This applies to

• A.

The Wilcoxon Test

• B.

The Mann Whitney U Test

A. The Wilcoxon Test
Explanation
The Wilcoxon Test is a non-parametric statistical test used to compare two related samples or matched pairs. It does not assume any specific distribution for the data. The null hypothesis in the Wilcoxon Test states that there is no difference between the two samples. If the observed value of T (the test statistic) is equal to or less than the critical value for a given level of significance, it means that the probability of obtaining such a result by chance is very low. Therefore, we can reject the null hypothesis and conclude that there is a significant difference between the two samples.

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• 19.

### A test of correlation suitable for use with pairs of scores. It can be used with ordinal data.

• A.

Spearman's Correlation Coefficient

• B.

The Chi Sqaured Test

A. Spearman's Correlation Coefficient
Explanation
Spearman's Correlation Coefficient is a suitable test of correlation for pairs of scores, including ordinal data. This test is used to determine the strength and direction of the relationship between two variables, regardless of whether the relationship is linear or not. It is a non-parametric test, meaning it does not rely on any assumptions about the distribution of the data. This makes it a versatile tool for analyzing data that may not meet the assumptions of other correlation tests. Therefore, Spearman's Correlation Coefficient is the correct answer for this question.

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• 20.

### If the observed value is equal to or greater than the critical value for a given level of significance, the null hypothesis can be rejected. This can be applied to

• A.

The Wilcoxon Test

• B.

Spearman's Correlation Coefficient

B. Spearman's Correlation Coefficient
Explanation
In Spearman's Correlation Coefficient, the null hypothesis states that there is no correlation between the two variables being compared. If the observed value is equal to or greater than the critical value for a given level of significance, it means that the correlation between the variables is statistically significant. Therefore, the null hypothesis can be rejected, indicating that there is a correlation between the variables. This is why the statement applies to Spearman's Correlation Coefficient.

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• 21.

### A test of association for use with data gathered from independent samples that are measured at a nominal level in the form of frequencies.

• A.

The Chi-Squared Test

• B.

The Mann Whitney U Test

A. The Chi-Squared Test
Explanation
The Chi-Squared Test is the correct answer because it is specifically designed to test for association between two variables when the data is gathered from independent samples measured at a nominal level in the form of frequencies. This test calculates the difference between the observed frequencies and the expected frequencies under the assumption of independence, and determines whether this difference is statistically significant. The Mann Whitney U Test, on the other hand, is used to compare two independent samples when the data is measured at an ordinal level or higher.

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• 22.

### If the observed value of x² is equal to or greater than the critical value for a given level of significance, the null hypothesis can be rejected. This applies to

• A.

Spearman's Correlation Coefficient

• B.

The Chi Squared Test

B. The Chi Squared Test
Explanation
If the observed value of xÂ² is equal to or greater than the critical value for a given level of significance, the null hypothesis can be rejected. This applies to the Chi Squared Test. This means that if the calculated chi squared value is equal to or greater than the critical value from the chi squared distribution table, we can reject the null hypothesis and conclude that there is a significant relationship between the variables being tested.

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• 23.

### A systematic research technique for analysing transcripts of interviews, documents or text (visual or written) including advertisements.

• A.

Content Analysis

• B.

Thematic Analysis

A. Content Analysis
Explanation
Content analysis is a systematic research technique used to analyze transcripts of interviews, documents, or text, including advertisements. It involves identifying and categorizing specific themes or patterns within the content to gain insights and draw conclusions. This method is commonly used in various fields, such as social sciences, media studies, and marketing research, to examine the content's meaning, purpose, and impact. Thematic analysis, on the other hand, focuses on identifying and interpreting themes within qualitative data. Therefore, content analysis is the correct answer in this context.

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• 24.

### A method for identifying, analyzing, and reporting patterns (themes) within data. It minimally organizes and describes your data set in detail. It involves taking a body of text and organizing it into specific themes so that the content can be summarised.

• A.

Thematic Analysis

• B.

Content Analysis

A. Thematic Analysis
Explanation
Thematic Analysis is a method used to identify, analyze, and report patterns or themes within a dataset. It involves organizing a body of text into specific themes, allowing for a summary of the content. This process provides a detailed description and organization of the data set, enabling researchers to gain insights and understand the underlying patterns or themes present in the data.

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• 25.

### Involves approaching the data with no preconceptions about which themes might emerge.

• A.

Inductive Analysis

• B.

Theoretical Analysis

A. Inductive Analysis
Explanation
Inductive analysis involves approaching the data with no preconceptions about which themes might emerge. This means that the researcher does not have any predetermined theories or hypotheses and instead allows the themes to emerge naturally from the data. In contrast, theoretical analysis involves using preexisting theories or frameworks to guide the analysis of the data. Therefore, the correct answer is Inductive Analysis.

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• 26.

### Usually means that the researcher already has some ideas about what themes may emerge, based on previous research, so they examine data to see whether these themes are present.

• A.

Semantic Thematic Analysis

• B.

Theoretical Analysis

B. Theoretical Analysis
Explanation
The given explanation suggests that the correct answer is "Theoretical Analysis" because it states that usually, researchers already have some ideas about what themes may emerge based on previous research, and they examine data to see if these themes are present. This aligns with the concept of theoretical analysis, where researchers use existing theories and knowledge to guide their analysis and interpretation of data.

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• 27.

### Looks at the meaning and form of text without going beyond this.

• A.

Latent Thematic Analysis

• B.

Semantic Thematic Analysis

B. Semantic Thematic Analysis
Explanation
Semantic Thematic Analysis is the correct answer because it refers to the process of analyzing the meaning and form of text without going beyond that. It focuses on understanding the themes and concepts present in the text, without delving into deeper or underlying meanings. This approach allows for a more surface-level analysis of the text, without considering any hidden or latent themes.

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• 28.

### Involves first analyzing themes at a semantic level and then ‘drilling down’ to try to understand why a text has been structured in a particular way.

• A.

Latent Thematic Analysis

• B.

Inductive Analysis

A. Latent Thematic Analysis
Explanation
Latent Thematic Analysis involves analyzing themes at a semantic level and then delving deeper to understand the underlying reasons for the structure of a text. This approach goes beyond surface-level analysis and aims to uncover the hidden or implicit meanings within a text. It involves identifying patterns, connections, and relationships between themes to gain a deeper understanding of the text's structure and the motivations behind it. Inductive Analysis, on the other hand, is a broader term that refers to any approach that starts with specific observations or data and then develops general conclusions or theories.

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• 29.

### Report Section: It should provide a clear indication of the focus of the study.

• A.

The Title

• B.

The Abstract

A. The Title
Explanation
The title of a report is crucial as it provides a concise and clear indication of the focus or topic of the study. It should capture the main idea or purpose of the report, allowing readers to quickly understand what the study is about. A well-written title helps in attracting the attention of potential readers and gives them an initial understanding of the report's content. Therefore, the title serves as an important element in providing a clear indication of the study's focus.

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• 30.

### Report Section: Provides a clear and concise account of the entire investigation, so that readers can gain an overview of the study and decide whether or not the rest of the report is likely to be of interest.

• A.

The Abstract

• B.

The Method

A. The Abstract
Explanation
The abstract is a summary of the entire report, providing a brief overview of the investigation. It allows readers to quickly understand the purpose, methods, and key findings of the study. By reading the abstract, readers can decide whether or not the report is relevant to their interests and worth further exploration.

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• 31.

### Report Section: It should review existing research literature in the area of interest and provide a clear foundation for the work to be undertaken.

• A.

Introduction, Aim(s) and Hypotheses

• B.

The Title

A. Introduction, Aim(s) and Hypotheses
Explanation
The correct answer is Introduction, Aim(s) and Hypotheses. This is because the introduction section of a research report is crucial as it sets the stage for the study by providing background information, stating the aim(s) of the research, and presenting the hypotheses that will be tested. It is important to review existing research literature in this section to establish a clear foundation for the work to be undertaken. The title of the report is also important, but it alone does not provide the necessary information about the research objectives and hypotheses.

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• 32.

### Report Section: Precise details are given about how the investigation was carried out.

• A.

The Abstract

• B.

The Method

B. The Method
Explanation
The correct answer is "The Method" because the report section mentioned that precise details were given about how the investigation was carried out. This indicates that the section discussing the methodology of the investigation, which is commonly referred to as "The Method," provides a thorough explanation of the research process and procedures followed during the investigation.

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• 33.

### Report Section: The Method Section is divided into which subsections:

• A.

Design, Participants, Apparatus/Materials and Procedure

• B.

Design, Sampling Methods and Processes

A. Design, Participants, Apparatus/Materials and Procedure
Explanation
The correct answer is "Design, Participants, Apparatus/Materials, and Procedure". In the Method section of a report, it is important to provide information about the design of the study, including the research design and any specific variables or conditions. The participants subsection should describe the characteristics of the individuals involved in the study, such as their demographics or any specific criteria for inclusion/exclusion. The apparatus/materials subsection should detail any equipment or materials used in the study, including any measurements or instruments. The procedure subsection should outline the steps taken to conduct the study, including any tasks or instructions given to participants.

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• 34.

### Report Section: This section will consist of appropriate descriptive and inferential statistics presented in summary tables and figures with brief descriptions.

• A.

Results

• B.

Appendices

A. Results
Explanation
The given correct answer is "Results". In a report, the Results section is where the findings of the study are presented. This section typically includes a summary of the data collected, the statistical analyses performed, and any significant findings or patterns observed. It may also include tables, figures, or graphs to visually represent the data. The Results section is crucial as it provides the reader with a clear understanding of the outcomes of the study and allows for the evaluation of the research objectives or hypotheses.

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• 35.

### Report Section: This section is used to review the findings, compare them to existing research, assess the overall quality of the study, and make suggestions about what research could be done next.

• A.

Discussion

• B.

Review

A. Discussion
Explanation
The given correct answer is "Discussion". In a research report, the discussion section is where the findings of the study are analyzed, interpreted, and discussed in relation to existing research. It provides an opportunity to compare the results with previous studies, evaluate the strengths and limitations of the study, and draw conclusions. The discussion section also offers suggestions for future research directions or areas that could be explored further.

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• 36.

### Report Section: There will usually be a brief section that sums up the main findings.

• A.

Results

• B.

Conclusion

B. Conclusion
Explanation
The given correct answer is "Conclusion". In a report, the conclusion section is typically included to summarize the main findings and provide a final statement or recommendation based on the results. It serves as a concise summary of the report's key points and helps the reader understand the overall significance and implications of the findings.

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• 37.

### Report Section: All the sources that the researcher used to inform the report, and are cited in it, must be included here.

• A.

Appendices

• B.

References

B. References
Explanation
The correct answer is "References" because the report section requires the inclusion of all the sources that the researcher used to inform the report and are cited in it. The references section is where these sources are listed in a standardized format, providing the necessary information for readers to locate and verify the information used in the report.

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• 38.

### Report Section: Published research occasionally has numbered appendices which might include raw data, statistical calculations, a copy of a questionnaire or interval schedule or other materials that would overload the main report.

• A.

The Results

• B.

Appendices

B. Appendices
Explanation
The answer "Appendices" is correct because the given passage mentions that published research sometimes includes numbered appendices. These appendices can contain various materials such as raw data, statistical calculations, questionnaires, or interval schedules. The purpose of including appendices is to avoid overloading the main report with excessive information.

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• 39.

### Good Practice in Reporting Research: Sharing research ideas and findings should never lead to researchers passing off other people’s work or ideas as their own. This is known as......

• A.

Avoiding Plagiarism

• B.

Using Primary Source Material

A. Avoiding Plagiarism
Explanation
The correct answer is "Avoiding Plagiarism." Plagiarism refers to the act of using someone else's work or ideas without giving them proper credit. In the context of reporting research, it is important for researchers to acknowledge and cite their sources to avoid plagiarism. By doing so, they demonstrate ethical conduct and maintain the integrity of their own work.

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• 40.

### Good Practice in Reporting Research: One way to guard against plagiarism and to improve the quality of your work is to use and acknowledge primary sources of information when writing a report. This is because inaccuracies can creep in as information is passed from one person to another. This is known as.........

• A.

Using Primary Source Material

• B.

Avoiding Plagiarism

A. Using Primary Source Material
Explanation
Inaccuracies can occur when information is passed from one person to another. By using primary source material, which is the original source of information, researchers can reduce the risk of inaccuracies and ensure the quality of their work. Additionally, acknowledging primary sources through proper citation and attribution helps to guard against plagiarism, as it gives credit to the original authors and avoids presenting their work as one's own.

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