Which Of The Following Research Methods Allows Us To Draw Cause-and-effect Relationships?

Descriptive Research

Descriptive research refers to the measurement of behaviors and attributes through ascertainment rather than through experimental testing.

Learning Objectives

Explain when descriptive enquiry is useful

Fundamental Takeaways

Key Points

• Descriptive studies practise non test specific relationships between factors; however, they provide information about behaviors and attributes with the goal of reaching a better agreement of a given topic.
• Descriptive research is a useful method of gathering information about rare phenomena that could non be reproduced in a laboratory or almost subjects that are non well understood.
• Descriptive research has the advantage of studying individuals in their natural environs, free from the influence of an experiment 'due south artificial construct.
• The most common type of descriptive research is the case study, which provides an in-depth analysis of a specific person, group, or phenomenon. While their findings cannot be generalized to the overall population, case studies can provide important data for hereafter research.

Key Terms

• case study: Enquiry performed in particular on a unmarried individual, group, incident, or community, equally opposed to (for example) a sample of the whole population.
• hypothesis: A tentative theorize explaining an observation, miracle, or scientific trouble that can be tested past farther observation and/or experimentation.

Inquiry studies that do not test specific relationships between variables are called descriptive studies. These studies are used to depict general or specific behaviors and attributes that are observed and measured. In the early stages of research it might exist difficult to form a hypothesis, specially when at that place is non any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not nonetheless clearly defined equally a hypothesis. Frequently a researcher will begin with a non-experimental approach, such every bit a descriptive study, to assemble more data virtually the topic before designing an experiment or correlational report to accost a specific hypothesis.

Descriptive enquiry is distinct from correlational research, in which psychologists formally exam whether a relationship exists between 2 or more variables. Experimental research goes a step further across descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these weather affect behavior. Correlational and experimental research both typically employ hypothesis testing, whereas descriptive enquiry does not.

Descriptive Research: While descriptive inquiry cannot exist generalized beyond the specific object of study, it can help psychologists gain more information about a topic, and formulate hypotheses for future experiments.

Descriptive research can be used to gain a vast, if oftentimes inconclusive, amount of information. It has the advantage of studying individuals in their natural environment without the influence of the artificial aspects of an experiment. This approach tin also exist used to document rare events or conditions that could non be reproduced in a laboratory.

Example Studies

Ane of import kind of descriptive research in psychology is the case report, which uses interviews, observation, or records to gain an in-depth agreement of a single person, grouping, or phenomenon. Although case studies cannot be generalized to the overall population (as can experimental inquiry), nor tin can they provide predictive ability (as tin correlational enquiry), they can provide extensive information for the development of new hypotheses for future testing and provide information almost a rare or otherwise hard-to-written report effect or condition.

Correlational Enquiry

Correlational research can be used to see if two variables are related and to make predictions based on this human relationship.

Learning Objectives

Interpret results using correlational statistics

Key Takeaways

Key Points

• At that place are some instances where experimental research is not an option for applied or ethical reasons. In these situations, correlational research can still be used to determine if ii variables are related.
• Correlations can be used to brand predictions nearly the likelihood of two variables occurring together.
• Correlation does not imply causation. Merely because ane factor correlates with another does not mean the first gene causes the other or that these are the only two factors involved in the relationship. Merely an experiment can institute cause and effect.

Cardinal Terms

• causation: The deed by which an effect is produced; in psychological research, the assumption that one variable leads to another.
• negative correlation: A human relationship between ii variables such that as one increases the other decreases. On a graph, a negative correlation will accept a negative slope.
• positive correlation: A relationship between 2 variables such that as one increases or decreases the other does the same. On a graph, a positive correlation will accept a positive slope.

Correlational studies are used to show the human relationship betwixt two variables. Unlike experimental studies, all the same, correlational studies can only testify that ii variables are related—they cannot make up one's mind causation (which variable causes a change in the other). A correlational report serves but to describe or predict behavior, non to explicate it. In psychological research, it is important to remember that correlation does non imply causation; the fact that two variables are related does not necessarily imply that one causes the other, and further research would need to be done to testify whatever kind of causal human relationship.

Positive and Negative Correlations

The attributes of correlations include strength and management. The strength, or degree, of a correlation ranges from -1 to +1 and therefore will be positive, negative, or zilch. Direction refers to whether the correlation is positive or negative. For example, two correlations of.78 and -.78 have the exact same forcefulness but differ in their directions (.78 is positive and -.78 is negative). In contrast, two correlations of.05 and.98 have the same direction (positive) but are very different in their force. Although.05 indicates a relatively weak relationship,.98 indicates an extremely strong relationship between two variables. A correlation of 0 indicates no relationship between the variables.

A positive correlation, such as.8, would mean that both variables increase together. You might expect to see a positive correlation between high schoolhouse GPA and college GPA—in other words, that those students with high grades in high school will likewise tend to accept high grades in higher.

A negative correlation, such as -.8, would mean that one variable increases equally the other increases. You might wait to see a negative correlation betwixt the amount of partying the night before a test and the score on that test—in other words, that more partying relates to a lower form.

Correlational Force

It is extremely rare to find a perfect correlation between two variables, but the closer the correlation is to -1 or +one, the stronger the correlation is.

Correlations of varying directions and strengths: Panels (a) and (b) show the difference between strong and weak positive linear patterns—the potent pattern more than closely resembles a directly line. The same is true for panels (c) and (d)—the strong negative linear pattern more closely resembles a straight line than does the weak negative pattern. Finally, comparing panels (a) and (c) shows the difference between positive and negative linear patterns—a positive linear pattern slopes up (both variables increase at the same time), and a negative linear design slopes downward (one variable decreases while the other increases).

Statistical Significance

Statistical testing must be done to determine if a correlation is significant. Fifty-fifty a seemingly potent correlation, such every bit.816, can actually be insignificant due to a diverseness of factors, such every bit random chance and the size of the sample being tested. With smaller sample sizes, it can be easy to obtain a large correlation coefficient but difficult for that correlation coefficient to attain statistical significance. In contrast, with large samples, even a relatively small correlation of.20 may achieve statistical significance.

Benefits of Correlational Research

An experiment is not always the most appropriate approach to answering a research question. Sometimes it is not possible to comport out a true experiment for applied or ethical reasons because it is impossible to manipulate the contained variable. If a researcher was to await at the psychological effects of long-term ecstasy employ, it would non be ethical to randomly assign participants to a condition of long-term ecstasy use. An experiment is also non feasible when examining the effects of personality and individual differences since participants cannot exist randomly assigned into these categories. Correlational enquiry allows a researcher to determine if there is a relationship between two variables without having to randomly assign participants to conditions.

The strength of correlational research is its predictive capabilities. With a large sample size, y'all can use ane variable to predict the likelihood of the other when at that place is a strong correlation between the two. For instance, you could take two measurements from 1,000 families—whether the father is an alcoholic and whether a son is an alcoholic—and summate the correlation. If there is a strong correlation between the two measurements, it volition permit you to predict, within certain limits of probability, what the chances are that the son of an alcoholic father volition too have a problem with booze.

Limitations of Correlational Enquiry

A correlational written report serves only to describe or predict behavior, not to explain it. Always retrieve that correlation does non imply causation. Since there is no random assignment to conditions, a researcher cannot rule out the possibility that in that location is a 3rd variable affecting the human relationship between the two variables measured. Even if at that place is no third variable, information technology is incommunicable to tell which gene is influencing the other. Only experimental enquiry can decide causation. In the above case, while a research could predict the likelihood of an alcoholic father having an alcoholic son, they could non describe why this was the case.

An splendid case used by Li (1975) to illustrate the "tertiary variable" trouble is the positive correlation in Taiwan in the 1970's between the use of contraception and the number of electric appliances in i'southward house. Of course, using contraception does not induce you to buy electrical appliances or vice versa. Instead, the third variable of instruction level affects both.

Another popular example is that there is a potent positive correlation between ice cream sales and murder rates in the summertime. Equally ice cream sales rise, then do murder rates. Is this because eating water ice cream makes us want to murder people? The actual explanation is that when the atmospheric condition is hot, more people purchase ice cream, but they also get out more, drink more than, and socialize more, leading to an increase in murder rates. Farthermost temperatures observed in the summer besides have been shown to increase aggression. In this case, there are many other variables at play that feed the correlation between murder rates and ice cream sales.

Experimental Research

Experimental research tests a hypothesis and establishes causation by using independent and dependent variables in a controlled surround.

Learning Objectives

Compare the function of the independent and dependent variable in experimental blueprint

Fundamental Takeaways

Key Points

• Experiments are generally the about precise studies and take the most conclusive ability. They are particularly effective in supporting hypotheses virtually cause and outcome relationships. However, since the atmospheric condition in an experiment are artificial, they may not utilize to everyday situations.
• A well-designed experiment has features that control random variables to make certain that the event measured is caused by the independent variable being manipulated. These features include random assignment, use of a control grouping, and use of a single or double-blind design.
• An experimenter decides how to manipulate the independent variable while measuring only the dependent variable. In a practiced experiment, just the contained variable will affect the dependent variable.

Key Terms

• dependent variable: The attribute or subject field of an experiment that is influenced past the manipulated attribute; an outcome measured to see the effectiveness of the treatment.
• independent variable: The variable that is changed or manipulated in a serial of experiments.
• random assignment: Random assignment of subjects to experimental and control atmospheric condition is a process used to evenly distribute the individual qualities of the participants across the weather.

Experimental research in psychology applies the scientific method to reach the iv goals of psychology: describing, explaining, predicting, and controlling behavior and mental processes. A psychologist can use experimental research to exam a specific hypothesis by measuring and manipulating variables. By creating a controlled environs, researchers tin test the effects of an independent variable on a dependent variable or variables.

For example, a psychologist may be interested in the bear on of video game violence on children'due south assailment. The psychologist randomly assigns some children to play a violent video game for 1 hour and other children to play a non-vehement video game for i 60 minutes. And then the psychologist observes the children socialize later on to determine if the children in the "violent video game" condition bear more than aggressively than the children in the "non-violent video game" condition. In this example, the contained variable is video game group. Our independent variable has two levels: violent video games and not-violent video games. The dependent variable is the affair that we want to measure—in this case, aggressive beliefs.

Independent and Dependent Variables

In an experimental study, the contained variable is the factor that the experimenter controls and manipulates. This variable is hypothesized to exist the cause of a item consequence of interest. The dependent variable, on the other hand, depends on the independent variable, and will change (or not) because of the independent variable. The dependent variable is the variable that we want to measure out (as opposed to dispense). In a elementary experiment, a researcher might hypothesize that cookies will make individuals complete a task quicker. In ane condition, participants will exist offered cookies if they complete a task, while in some other status they will not exist offered cookies. In this case the presence of a reward (receiving cookies or non) is the independent variable, and the time taken to complete the task is the dependent variable.

Effect of a Reward: Furnishings of receiving a cookie equally a reward (contained variable) on fourth dimension taken to complete task (dependent variable). As shown in the figure, participants who received a cookie took much less time to complete the job than participants who did not receive a cookie.

An experiment tin can accept more than ane independent variable. A researcher might decide to test the hypothesis that cookies will make individuals piece of work harder but if the task is easy to begin with. In this case, both the presence of a reward and the difficulty of the task would be independent variables.

Experimental Design

The purpose of an experiment is to investigate the relationship between two variables to examination a hypothesis. By using the scientific method, a psychologist can program and design an experiment that will answer the research question. The bones steps of experimental design are:

• Identifying a question and performing preliminary inquiry to decide what is already known
• Creating a hypothesis
• Identifying and defining the contained and dependent variables
• Determining how the contained variable will be manipulated and how the dependent variable will be measured

The Scientific Method: The scientific method is the process by which new scientific knowledge is gained and verified. Commencement you must identify a question and, after some preliminary inquiry, form a hypothesis to respond that question. Later on designing an experiment to exam the hypothesis and collecting data from the experiment, a scientist will draw a determination. The conclusion will either support the hypothesis or refute it. The scientist will then either reformulate the hypothesis or build upon the original hypothesis. The scientific method cannot prove a hypothesis, only support or refute information technology.

Experimental Blueprint: Of import Principles

A poorly designed study volition not produce reliable data. At that place are key components that must be included in every experiment: the inclusion of a comparison grouping (known equally a "control group"), the utilise of random assignment, and efforts to eliminate bias. When a study is designed properly, the only difference between groups is the one made by the researcher.

Command Groups

Control groups are used to determine if the independent variable actually affects the dependent variable. The control group demonstrates what happens when the independent variable is non applied. The control grouping helps researchers balance the effects of being in an experiment with the effects of the independent variable. This helps to ensure that there are no random variables also influencing beliefs. In an experiment monitoring productivity, for instance, it was hypothesized that boosted lighting would increase productivity in factory workers. When workers were observed in additional lighting they were more productive, but just because they were being watched. If a command grouping was also observed with no additional lighting this effect would have been obvious.

Random Assignment

To minimize the chances that an unintended variable influences the results, subjects must be assigned randomly to different treatment groups. Random assignment is used to ensure that any preexisting differences among the subjects practice not impact the experiment. Past distributing differences randomly between the weather condition, random assignment lowers the chances that factors similar historic period, socioeconomic status, personality measures, and other individual variables will bear on the overall group's response to the contained variable. Theoretically, the baseline of both the experimental and control groups volition be the aforementioned before the experiment starts. Therefore, if in that location is a deviation in the beliefs of the ii groups at the finish of the experiment, the only reason would be the handling given to the experimental group. In this manner, an experiment can prove a cause-and-effect connexion between the independent and dependent variables.

Blinding and Experimenter Bias

To preserve the integrity of the control group, both researcher(s) and subject(s) may be "blinded." If a researcher expects certain results from an experiment and accordingly unknowingly influences the subjects' responses, this is called need bias. If the experimenter inadvertently interprets the information in a way that supports the hypothesis when other interpretations are possible, it is called the expectancy issue. To annul experimenter bias, the subjects can exist kept uninformed on the intentions of the experiment, which is called single blinding. If the people collecting the information and the participants are kept uninformed, then it is called a double bullheaded experiment. By using blinding, a researcher tin can eliminate the chances that they are inadvertently influencing the issue of the experiment.

Counterbalancing

When running an experiment, a researcher will want to pay close attention to their design to avoid error that tin can be introduced by not balancing the weather condition properly. Consider the following case. You are running a study in which participants complete a task of pressing push A with their left hand if they see a light-green light and pressing button B with their correct hand if they see a red light. You find back up for your hypothesis that red stimuli are processed more chop-chop than green stimuli. However, an alternative explanation is that people are faster to respond with their right manus just because most people are right-handed. The solution to this problem is to "counterbalance" your pattern. You will randomly assign fifty% of your participants to respond to the ruby-red stimulus with their correct hand (and green with their left) and assign the other 50% to respond to the red stimulus with their left hand (and green with their right). In this style, you are anticipating and controlling for this extra source of error in your design.

Strengths and Weaknesses of Experimental Enquiry

One of the primary strengths of experimental research is that it tin often determine a cause and issue relationship between ii variables. By systematically manipulating and isolating the independent variable, the researcher can determine with confidence the independent variable's causal effect on the dependent variable. Another forcefulness of experimental enquiry is the ability to assign participants to different weather condition through random consignment. Randomly assigning participants to conditions ensures that each participant is as likely to be assigned to 1 condition or another, and that in that location are no differences between experimental groups.

Although experimental enquiry can oft answer the causality questions that are left unclear by correlational studies, this is not always the case. Sometimes experiments may non exist possible or ethical. Consider the example of the studying the correlation between playing fierce video games and aggressive behavior. It would be unethical to assign children to play lots of fierce video games over a long menses of time to meet if information technology had an bear on on their aggression. Additionally, because experimental research relies on controlled, bogus environments, it can at times be difficult to generalize to existent world situations, depending on the experiment's design and sample size. If this is the case, the experiment is said to have poor external validity, meaning that the situation the participants were exposed to bears piddling resemblance to any real-life situation.

Source: https://courses.lumenlearning.com/boundless-psychology/chapter/types-of-research-studies/

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