Range of specified number Complete Incomplete Values Values are obtained by counting. Values are obtained by measuring. Classification Non-overlapping Overlapping Assumes Distinct or separate values. Any value between the two values. Represented by Isolated points Connected points. A discrete variable is a type of statistical variable that can assume only fixed number of distinct values and lacks an inherent order. Also known as a categorical variable , because it has separate, invisible categories.
However no values can exist in-between two categories, i. So, the number of permitted values that it can suppose is either finite or countably infinite. Hence if you are able to count the set of items, then the variable is said to be discrete. Continuous variable, as the name suggest is a random variable that assumes all the possible values in a continuum.
Simply put, it can take any value within the given range. So, if a variable can take an infinite and uncountable set of values, then the variable is referred as a continuous variable. A continuous variable is one that is defined over an interval of values, meaning that it can suppose any values in between the minimum and maximum value. A correlation is a statistical indicator of the relationship between variables.
Causation means that changes in one variable brings about changes in the other; there is a cause-and-effect relationship between variables. The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not. A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.
Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly. Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.
You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias.
Randomization can minimize the bias from order effects. Questionnaires can be self-administered or researcher-administered. Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.
Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions. A research design is a strategy for answering your research question. It defines your overall approach and determines how you will collect and analyze data. The priorities of a research design can vary depending on the field, but you usually have to specify:.
A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources. This allows you to draw valid , trustworthy conclusions. Quantitative research designs can be divided into two main categories:.
Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs. Correlation coefficients always range between -1 and 1. The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions.
The absolute value of a number is equal to the number without its sign. The absolute value of a correlation coefficient tells you the magnitude of the correlation: the greater the absolute value, the stronger the correlation. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes. In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.
This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings e. Triangulation means using multiple methods to collect and analyze data on the same subject. By combining different types or sources of data, you can strengthen the validity of your findings. These are four of the most common mixed methods designs :. Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.
But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples. In multistage sampling , you can use probability or non-probability sampling methods. For a probability sample, you have to probability sampling at every stage.
You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study. Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.
Scientists and researchers must always adhere to a certain code of conduct when collecting data from others. These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.
Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe. Both are important ethical considerations. You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.
You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals. Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.
Want to contact us directly? No problem. We are always here for you. Scribbr specializes in editing study-related documents. We proofread:. You can find all the citation styles and locales used in the Scribbr Citation Generator in our publicly accessible repository on Github.
Frequently asked questions See all. Home Frequently asked questions What is the difference between discrete and continuous variables? What is the difference between discrete and continuous variables? Discrete and continuous variables are two types of quantitative variables : Discrete variables represent counts e. Continuous variables represent measurable amounts e. What is sampling? Reliability and validity are both about how well a method measures something: Reliability refers to the consistency of a measure whether the results can be reproduced under the same conditions.
Validity refers to the accuracy of a measure whether the results really do represent what they are supposed to measure. What is the difference between internal and external validity?
What is experimental design? To design a controlled experiment, you need: A testable hypothesis At least one independent variable that can be precisely manipulated At least one dependent variable that can be precisely measured When designing the experiment, you decide: How you will manipulate the variable s How you will control for any potential confounding variables How many subjects or samples will be included in the study How subjects will be assigned to treatment levels Experimental design is essential to the internal and external validity of your experiment.
What are independent and dependent variables? For example, in an experiment about the effect of nutrients on crop growth: The independent variable is the amount of nutrients added to the crop field.
The dependent variable is the biomass of the crops at harvest time. What is the difference between quantitative and categorical variables? What is a confounding variable? How do I decide which research methods to use? If you want to measure something or test a hypothesis , use quantitative methods. If you want to explore ideas, thoughts and meanings, use qualitative methods. If you want to analyze a large amount of readily-available data, use secondary data.
If you want data specific to your purposes with control over how it is generated, collect primary data. If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods. What is mixed methods research? What is internal validity? What are threats to internal validity? What is the difference between a longitudinal study and a cross-sectional study?
What are the pros and cons of a longitudinal study? What is an example of a longitudinal study? How long is a longitudinal study? Why do a cross-sectional study? What are the disadvantages of a cross-sectional study? What is external validity? What are the two types of external validity? What are threats to external validity? Why are samples used in research? When are populations used in research?
What is sampling error? What is sampling bias? Why is sampling bias important? What are some types of sampling bias? How do you avoid sampling bias? What is probability sampling? What is non-probability sampling? Why are independent and dependent variables important?
What is an example of an independent and a dependent variable? The type of soda — diet or regular — is the independent variable.
The level of blood sugar that you measure is the dependent variable — it changes depending on the type of soda. Can a variable be both independent and dependent? Can I include more than one independent or dependent variable in a study? Why do confounding variables matter for my research? What is the difference between confounding variables, independent variables and dependent variables?
How do I prevent confounding variables from interfering with my research? What is data collection? What are the benefits of collecting data? When conducting research, collecting original data has significant advantages: You can tailor data collection to your specific research aims e. What is operationalization? What is hypothesis testing? What are the main qualitative research approaches? There are five common approaches to qualitative research : Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organization to understand its culture. Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Action research links theory and practice in several cycles to drive innovative changes. How do you analyze qualitative data? There are various approaches to qualitative data analysis , but they all share five steps in common: Prepare and organize your data. Review and explore your data. Develop a data coding system.
Assign codes to the data. Identify recurring themes. What is a Likert scale? Are Likert scales ordinal or interval scales? What is the difference between a control group and an experimental group? Do experiments always need a control group? What is blinding?
What is the difference between single-blind, double-blind and triple-blind studies? In a single-blind study , only the participants are blinded. In a double-blind study , both participants and experimenters are blinded. In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.
Why is blinding important? What is a quasi-experiment? When should I use a quasi-experimental design? What is simple random sampling? Embed Size px. Start on. Show related SlideShares at end. WordPress Shortcode. Next SlideShares. Download Now Download to read offline and view in fullscreen. Download Now Download Download to read offline.
Continuous and discontinuous variable Download Now Download Download to read offline. Sivasangari Shanmugam Follow. Assistant Professor.
Microbial growth. Thin layer chromatography. Paper chromatography. Gene transfer. Principle and Uses of Microbiological instruments. Swiss pdb viewer. Related Books Free with a 30 day trial from Scribd. Business Analysis Debra Paul. Python Machine Learning Sebastian Raschka. Dynamic Models in Biology Stephen P. Data Visualization: a successful design process Andy Kirk. Data Visualization with d3. Jaimon Johnson. Saroj Gangwar. Show More. Views Total views.
Actions Shares.
0コメント