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What is the difference between a control group and an experimental group?
An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not, dissertation control groups.
They should be identical in all other ways. Methodology refers to the overarching strategy and rationale of your research project. It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives. Methods are the specific tools and procedures you use to collect and analyze data for example, experiments, surveysand statistical tests.
In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section.
In a longer or more complex research project, dissertation control groups, such as a thesis or dissertationyou will probably include a methodology sectionwhere you explain your approach to answering the research questions and cite relevant sources to support your choice of methods. Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses. Qualitative methods allow you to explore concepts dissertation control groups experiences in more detail.
A sample is a subset of individuals from a larger population, dissertation control groups. Sampling means selecting the group that you will actually collect data from in your research.
For example, if you are researching the opinions of students in your university, you could survey a sample of students. In statistics, sampling allows you to test a hypothesis about the characteristics of a population. Reliability and validity are both about how well a method measures something:. If you are doing experimental research, you also have to consider the internal and external validity of your experiment.
I nternal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables. External validity is the extent to which your results can be generalized to other contexts. The validity of your experiment depends on your experimental design. Experimental design means planning a set of procedures to investigate a relationship between variables. To design a dissertation control groups experiment, you need:.
Experimental design is essential to the internal and external validity of your experiment. You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the causewhile a dependent variable is the effect.
In an experiment, dissertation control groups manipulate the independent variable and measure the outcome in the dependent variable. Dissertation control groups example, in an experiment about the effect of nutrients on crop growth:. Defining your variables, and deciding how you will manipulate and measure them, dissertation control groups, is an important part of experimental design.
Quantitative variables are any variables where the data represent amounts e. height, weight, or age. Categorical variables are any variables where the data represent groups. This includes rankings e. finishing places in a raceclassifications e. brands of cerealand binary outcomes e. coin flips, dissertation control groups.
You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results. Discrete and continuous variables are two types of quantitative variables :. A confounding variablealso called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship. A confounding variable is related to both the supposed cause and the supposed effect of dissertation control groups study.
It can be difficult to separate the dissertation control groups effect of the independent variable from the effect of the confounding variable. The research methods you use depend on the type of data you need to answer your research question. In mixed methods researchyou use both qualitative and quantitative data collection and analysis methods to answer your research question. Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors, dissertation control groups.
There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias, regression to the mean, social interaction and attrition. Longitudinal studies and cross-sectional studies are two different types of research design. In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.
Longitudinal studies are better to establish the correct sequence of events, dissertation control groups, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.
The British Cohort Studywhich has collected data on the lives of 17, Brits since their births inis one well-known example of a longitudinal study. Longitudinal studies can last anywhere from weeks dissertation control groups decades, although they tend to be at least a year long.
Cross-sectional studies are less expensive and time-consuming than many other types of study. Sometimes dissertation control groups cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it.
Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study.
The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures. The two types of external validity are population validity whether you can generalize to other groups of people and ecological validity whether you can generalize to other situations and settings.
There are seven threats to external validity : selection bias, history, experimenter effect, Hawthorne effect, testing effect, aptitude-treatment and situation effect. Samples are used to make inferences about populations. Samples are easier to collect data from because they are practical, cost-effective, dissertation control groups, convenient and manageable. Populations are used when a research question requires data from every member of the population.
This is usually only feasible when the population is small and easily accessible. A statistic refers to measures about the samplewhile a parameter refers to measures about the population.
A sampling error is the difference between a population parameter and a sample statistic. Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others. Sampling bias is a threat to external validity — it limits the generalizability of your findings to a broader group of people.
Some common types of sampling bias include self-selection, non-response, undercoverage, survivorship, pre-screening or advertising, and healthy user dissertation control groups. Using careful research design and sampling procedures can help you avoid sampling bias. Oversampling can be used to correct undercoverage bias. Probability sampling means that every member of the target population has a known chance of being included in the sample.
Probability sampling methods include simple random samplingsystematic samplingstratified samplingand cluster sampling. In non-probability samplingthe sample is selected based on non-random criteria, and not every member of the population has a chance of being included. Common non-probability sampling methods include convenience sampling, voluntary response sampling, purposive sampling, snowball sampling, and quota sampling.
Determining cause and effect is one of the most important parts of dissertation control groups research. You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment.
The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!
Yes, but including more than one of either type requires multiple research questions. Dissertation control groups example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, dissertation control groups, pulse, and many more.
Each of these is its own dependent variable with its own research question. You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable. To ensure the internal dissertation control groups of an experimentyou should only change one independent variable at a time. To ensure the internal validity of your research, you must consider the impact of confounding variables.
If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variablesor even find a causal relationship where none exists. A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed causewhile the dependent variable is the supposed effect. A confounding variable is a third variable that influences both the independent and dependent variables.
Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables. There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization. In restrictionyou restrict your sample by dissertation control groups including certain subjects that have the same values of potential confounding variables. In matchingyou match each of the subjects in your dissertation control groups group with a counterpart in the comparison group.
The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable. In statistical controlyou include potential confounders as variables in your regression. In randomizationyou randomly assign the treatment or independent variable in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations. However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive, dissertation control groups. Operationalization means turning abstract conceptual ideas into measurable observations.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypothesesby calculating how likely it is that a pattern or relationship between variables could have arisen by chance, dissertation control groups. There are five common approaches to qualitative research :, dissertation control groups. There are various approaches to qualitative data analysisbut they all share five steps in common:.
Control and Variable Groups
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