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2021-05-14

What happens when other scientists achieve different results when repeating an investigation?

What happens when other scientists achieve different results when repeating an investigation?

Summary. Getting the same result when an experiment is repeated is called replication. Replication is important in science so scientists can “check their work.” The result of an investigation is not likely to be well accepted unless the investigation is repeated many times and the same result is always obtained.

Why does repeating an experiment make it more accurate?

Repeating an experiment more than once helps determine if the data was a fluke, or represents the normal case. It helps guard against jumping to conclusions without enough evidence. The number of repeats depends on many factors, including the spread of the data and the availability of resources.

Should experiments be repeated over and over to see if the results are the same each time?

Experiments should be repeated to see if the same results are obtained each time. This gives validity to the test results.

Why would you repeat an experiment over and over again?

By repeating the experiment over and over, we can see if our result really supports our hypothesis (What is a Hypothesis?), or if it was just random chance. Sometimes the result might be due to some variable that you have not recognized. Results that don’t fit are important!

How many times should you repeat an experiment to know if the hypothesis is true?

For a typical experiment, you should plan to repeat the experiment at least three times. The more you test the experiment, the more valid your results.

Is validity the same as accuracy?

They indicate how well a method, technique or test measures something. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure

What is the relationship between validity and reliability?

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).

Which of the following is a threat to internal validity?

There are eight threats to internal validity: history, maturation, instrumentation, testing, selection bias, regression to the mean, social interaction and attrition

How can we prevent threats to internal validity?

Avoid assigning subjects to groups based on their extreme scores. Recruit large groups of participants or more than needed for statistical analyses. Include incentives and compensation as appropriate. Utilize random selection (sampling) and random assignment of subjects.

What is the difference between internal and external validity?

Internal validity refers to the degree of confidence that the causal relationship being tested is trustworthy and not influenced by other factors or variables. External validity refers to the extent to which results from a study can be applied (generalized) to other situations, groups or events

How can internal and external validity be improved?

Increasing Internal and External Validity In group research, the primary methods used to achieve internal and external validity are randomization, the use of a research design and statistical analysis that are appropriate to the types of data collected, and the question(s) the investigator(s) is trying to answer.

What is meant by internal validity?

Internal validity is defined as the extent to which the observed results represent the truth in the population we are studying and, thus, are not due to methodological errors.

How does history affect internal validity?

To affect the outcome of an experiment in a way that threatens its internal validity, a history effect must (a) change the scores on the independent and dependent variables, and (b) change the scores of one group more than another (e.g., increase the scores of the treatment group compared with the control group or a …

How does bias affect validity?

The internal validity, i.e. the characteristic of a clinical study to produce valid results, can be affected by random and systematic (bias) errors. Bias cannot be minimised by increasing the sample size. Most violations of internal validity can be attributed to selection bias, information bias or confounding

How is testing a threat to internal validity?

During the selection step of the research study, if an unequal number of test subjects have similar subject-related variables there is a threat to the internal validity. The subjects in both groups are not alike with regard to the independent variable but similar in one or more of the subject-related variables.

Does selection bias affect internal validity?

Selection bias can affect either the internal or the external validity of a study. Selection bias adversely affecting internal validity occurs when the exposed and unexposed groups (for a cohort study) or the diseased and nondiseased groups (for a case-control study) are not drawn from the same population.

What are the 3 types of bias?

Three types of bias can be distinguished: information bias, selection bias, and confounding. These three types of bias and their potential solutions are discussed using various examples.

What are the two main types of bias?

A bias is the intentional or unintentional favoring of one group or outcome over other potential groups or outcomes in the population. There are two main types of bias: selection bias and response bias. Selection biases that can occur include non-representative sample, nonresponse bias and voluntary bias

What are the 2 types of bias?

The different types of unconscious bias: examples, effects and solutions

  • Unconscious biases, also known as implicit biases, constantly affect our actions.
  • Affinity Bias.
  • Attribution Bias.
  • Attractiveness Bias.
  • Conformity Bias.
  • Confirmation Bias.
  • Name bias.
  • Gender Bias.

What are the 5 types of bias?

We have set out the 5 most common types of bias:

  1. Confirmation bias. Occurs when the person performing the data analysis wants to prove a predetermined assumption.
  2. Selection bias. This occurs when data is selected subjectively.
  3. Outliers. An outlier is an extreme data value.
  4. Overfitting en underfitting.
  5. Confounding variabelen.

What is an example of bias?

Bias is an inclination toward (or away from) one way of thinking, often based on how you were raised. For example, in one of the most high-profile trials of the 20th century, O.J. Simpson was acquitted of murder. Many people remain biased against him years later, treating him like a convicted killer anyway.

What are some common biases?

12 Common Biases That Affect How We Make Everyday Decisions

  • The Dunning-Kruger Effect.
  • Confirmation Bias.
  • Self-Serving Bias.
  • The Curse of Knowledge and Hindsight Bias.
  • Optimism/Pessimism Bias.
  • The Sunk Cost Fallacy.
  • Negativity Bias.
  • The Decline Bias (a.k.a. Declinism)

What are the 7 types of cognitive biases?

While there are literally hundreds of cognitive biases, these seven play a significant role in preventing you from achieving your full potential:

  • Confirmation Bias.
  • Loss Aversion.
  • Gambler’s Fallacy.
  • Availability Cascade.
  • Framing Effect.
  • Bandwagon Effect.
  • Dunning-Kruger Effect.

What are the 12 cognitive biases?

  • 12 Cognitive Biases That Can Impact Search Committee Decisions.
  • Anchoring Bias.
  • Availability Bias.
  • Bandwagon Effect.
  • Choice-supportive Bias.
  • Confirmation Bias.
  • Fundamental. Attribution Error.
  • Halo Effect.

What are personal biases?

Unconscious biases, also known as implicit biases, are the underlying attitudes and stereotypes that people unconsciously attribute to another person or group of people that affect how they understand and engage with a person or group.