SAS (Statistical Analysis Software) – is a statistical analysis platform that offers options to use either the GUI, or to create scripts for more advanced analyses. It is a premium solution that is widely used in business, healthcare, and human behavior research alike. It’s possible to carry out advanced analyses and produce publication-worthy graphs and charts, although the coding can also be a difficult adjustment for those not used to this research.

GraphPad Prism – is a premium software primarily used within statistics related to biology, but offers a range of capabilities that can be used across various fields. Similar to SPSS, scripting options are available to automate analyses, or carry out more complex statistical calculations, but the majority of the work can be completed through the GUI.

Minitab – offers a range of both basic and fairly advanced statistical tools for data analysis. Similar to GraphPad Prism, commands can be executed through both the GUI and scripted commands, making it accessible to novices as well as users looking to carry out more complex analyses.

SPSS – used within human behavior research. SPSS offers the ability to easily compile descriptive statistics, parametric and non-parametric analyses, as well as graphical depictions of results through the graphical user interface (GUI. It also includes the option to create scripts to automate analysis, or to carry out more advanced statistical processing.

R (R Foundation for Statistical Computing) – Free statistical software package that is widely used across both human behavior research and in other fields. Toolboxes (essentially plugins) are available for a great range of applications, which can simplify various aspects of data processing. While R is a very powerful software, it also has a steep learning curve, requiring a certain degree of coding. It does however come with an active community engaged in building and improving R and the associated plugins, which ensures that help is never too far away.

MatLab – is an analytical platform and programming language that is widely used by engineers and scientists. As with R, the learning path is steep, and you will be required to create your own code at some point. A plentiful amount of toolboxes are also available to help answer your research questions (such as EEGLab for analyzing EEG data). While MatLab can be difficult to use for novices, it offers a massive amount of flexibility in terms of what you want to do – as long as you can code it (or at least operate the toolbox you require).

To prepare a research proposal:

1. Provide an outline of the general area of study within which your research falls
2. Refer to how much is currently known about the topic
3. Highlight any recent debate or conversation around the topic by other academics

The content that should be included in your proposal:

1. Title page – Provide working title of your research in concern
2. Abstract – Give a concise notion of the study
3. Research problem – Discuss problems that you want to study and the significance of doing so
4. Literature review – Lay down your awareness of the essential literatures in your topic; identifying the present gaps
5. Important research objectives – Identify a research problem. Post at least 3 research objectives
6. Methodology – This elements talks about the way you are going to perform the research while also providing the reason why
7. Timeframe – Delineate the time frame of your research

Validity is defined as the degree of agreement between the claimed measurement and the real world.

There are four categories of validity test, namely:

1. Content validity – Seeks to answer the question of whether the current test covers all relevant items needed to answer the research question.
2. Criterion validity – Degree of correlation between the current test to the predetermined standard. The predetermined standard scores are those that had been tested by prior studies and had been held to be valid.
3. Construct validity – Degree to which the test actually measures what the theory claims.
4. Face validity – Use the respondents to answer the question: Does the survey or test measure what it intended to measure? This is the subjective view of the respondents to the survey (not experts). use this as a test-run before distributed the real survey.

A population is the entire group that you want to draw conclusion about.

A sampling frame is a list of all the items in your population. The specific group that you will collect data from. The size of the sample is always less than the total size of the population.

In research, a population doesn’t always refer to people. It can mean a group containing elements of anything you want to study, such as objects, events, organizations, countries, species, organisms, etc.

The difference between a population and a sampling frame is that the population is general and the frame is specific.

Probability sampling:

Simple random sampling – It is reliable method of obtaining information where every single member of a population is chosen randomly, merely by chance. Each individual has the same probability of being chosen to be a part of a sample.

Cluster sampling – Cluster sampling is a method where the researchers divide the entire population into section or clusters that represent a population.

Systematic sampling – Researchers use the systematic sampling method to choose the sample members of a population at regular intervals.

Stratified random sampling – Stratified random sampling is a method in which the researcher divide the population into smaller groups that don’t overlap but represent the entire population.

Non-probability sampling:

Convenience sampling – This method is dependent on the ease of access to subjects such as surveying customers at a mall or passers-by on a busy street.

purposive sampling – formed by the discretion of the researcher. researchers purely consider the purpose of the study, along with the understanding of the target.

Snowball sampling – sampling method that researchers apply when the subjects are difficult to trace. For example, it will be extremely challenging to survey shelter less people or illegal immigrants.

Quota sampling – In Quota sampling, the selection of members in this sampling technique happens based on a pre-set standard. In this case, as a sample is formed based on specific attributes, the created sample will have the same qualities found in the total population. It is a rapid method of collecting samples.

Degree of predetermined nature:

Quantitative – Predetermined; Mixed – Both predetermined and emerging methods; Qualitative – Emerging methods

Questions:

Quantitative – Instrument based; Mixed – Both open- and closed-ended; Qualitative – Open-ended

Data types:

Quantitative – Performance, attitude, observation and census; Mixed – Multiple forms of data drawing on all possibilities; Qualitative – Interview, observation, document, and audiovisual

Analysis:

Quantitative – Statistical analysis, Mixed – Statistical and text analysis; Qualitative – Text and image analysis

Interpretation:

Quantitative – Statistical interpretation; Mixed – Across databases interpretation; Qualitative – Themes, patterns interpretation

May employ these strategies of inquiry:

Quantitative – Surveys, experiments; Mixed – Sequential, convergent, and embedded; Qualitative – Phenomenology, grounded theory, ethnography, case studies, narrative

How to decide the research sample size?

1. Choose an appropriate significance level (alpha value). An alpha value of p=.05 is commonly used. This means that the probability that the results found are due to chance alone is 0.05, or 5%, and 95% of the time a difference found between the control group and the experimental group will be statistically significant and due to the manipulation or treatment.
2. Select the power level. Typically a power level of .8, or 80%, is chosen. This means that 80% of the time the experiment will detect a difference between the control and experimental groups if a difference actually exists.
3. Estimate the effect size. Generally, a moderate to large effect size of 0.5 or greater is acceptable for clinical research. this means that the difference resulting from the manipulation, or treatment, would account for about one half of a standard deviation in the outcome.
4. Organize your existing data. With the values for the three factors available, refer to the table in your statistician’s manual or textbook; or enter the three values into an online calculator made for determining sample size.

The scope of a study explains the extent to which the research area will be explored in the work and specifies the parameters within the study will be operating.

Basically, this means that you will have to define what the study is going to cover and what it is focusing on. Similarly, you also have to define what the study is not going to cover. This will come under the limitations. generally, the scope of a research paper is followed by its limitations.

as a researcher, you have to be careful when you define your scope or area of focus. remember that if you broaden the scope too much, you might not be able to do justice to the work or it might take a very long time to complete. Consider the feasibility of your work before you write down the scope. Again, if the scope is too narrow, the findings might not be generalizable.

Typically, the information that you need to include in the scope would cover the following:

1. General purpose of the study.
2. The population or sample that you are study.
3. The duration of the study.
4. The topics or theories that you will discuss.
5. The geographical location covered in the study.

Time period: While writing the scope of the study the researcher should first mention or state categorically the time periods the study will cover. Generally, the researchers combine the scope of the study with the limitation of the study.

Geography: In addition to this another major point where the researcher should keep in mind that scope of the study should state the specific aspect of the data that needs to be collected like the geographic locations and the variables.

Research population: another major aspect that should be involved while writing the scope of the study is the sample size or the population that the researcher has selected for the study.

Theories: The researcher should state the academic theories that are being applied to the data collected so that the reader better knows the lens of the analysis.

Purpose: The scope of the study must indicate the purpose behind it. It must briefly define the larger picture, i.e. the overall goal the researcher is trying to achieve.

Limitations: It is impossible to avoid roadblocks in research. Every research is restricted in scope and is subjected to certain limitations. By acknowledging these limitations and how they are restricting the study makes its findings even more credible.

Steps:

1. Conduct a search – The published scientific literature is indexed in a variety of databases. Search these databases of studies. It is important to search numerous databases to ensure that the majority of relevant studies have been identified.
2. Identify keywords – Authors call out several keywords when publishing their research so others can identify the work during database searches. Once you find a relevant article, use its keywords and similar ones in your search.
3. Review Abstracts and Articles – After the search is complete and all duplicates are throw out, it is time to review the abstracts of the remaining articles to ensure that they address your review questions. With narrative reviews, it is not necessary to include every article on a topic.
4. Document Results – Summarize and synthesize the findings from the articles you have found, and integrate then into your writing as appropriate. You do not need to document your literature search. reference the articles as you use information from the studies.