A testable prediction is known as a [Blank 1]. Researchers may use [Blank 2] to discover if the results of a study are accurate. To try and make certain that there are no pre-existing differences between [Blank 3] in an experiment, researchers use [Blank 4] assignment. [Blank 5] is not necessarily causation. Beware of [Blank 6] coated journalism where numbers are used to convey the aura of science, but the methods used to collect them are [Blank 7]. Prompts Blank 1 Submitted Answers Hypothesis Blank 2 Choose a match Blank 3 Groups Blank 4 Choose a match Blank 5 Choose a match Last saved 4:38:43 PM Questions Filter (4)
The Correct Answer and Explanation is:
- Hypothesis
A testable prediction is known as a hypothesis. It is a statement or educated guess that predicts the outcome of an experiment based on prior knowledge, observations, or theory. For example, “If I water a plant with more water, it will grow taller” is a hypothesis. The hypothesis must be specific and measurable, allowing scientists to conduct experiments that test whether it is true or false. - Statistical tests
Researchers may use statistical tests to discover if the results of a study are accurate. Statistical tests help to analyze the data collected during an experiment, allowing researchers to determine whether the observed effects are significant or could have occurred by chance. Common statistical tests include t-tests, chi-squared tests, and ANOVA, depending on the type of data and the hypothesis being tested. These tests provide p-values that help scientists understand the likelihood that their results reflect a true effect, rather than random variability. - Groups
To try and make certain that there are no pre-existing differences between groups in an experiment, researchers use random assignment. Random assignment is a technique where participants are randomly assigned to different groups (such as experimental and control groups). This ensures that each participant has an equal chance of being assigned to any group, minimizing bias and helping to establish a cause-and-effect relationship between variables. Random assignment helps prevent systematic differences between groups that could skew the results. - Random
Random assignment is the process by which participants are randomly assigned to different groups in an experiment. This procedure helps ensure that no external factors (such as age, gender, or background) influence the results, making the study more reliable. Random assignment is critical in experimental research to maintain internal validity and reduce potential confounding variables. - Correlation
Correlation is not necessarily causation. While two variables may be correlated (i.e., they change together), it does not imply that one causes the other. For example, the number of ice cream sales may be correlated with the number of drownings in a location, but it doesn’t mean that buying ice cream causes drowning. A third factor, such as the warmer weather, might influence both. - Sensationalized
Beware of sensationalized journalism, where numbers are used to convey the aura of science, but the methods used to collect them are flawed. Sensationalized journalism can mislead the public by using scientific-sounding language, while often glossing over or misrepresenting the research methods or results. It is essential to scrutinize how data is collected, analyzed, and presented, as inaccurate methods can lead to misleading conclusions. - Flawed
The methods used to collect data in sensationalized journalism are often flawed. Researchers may use small sample sizes, cherry-pick data, or fail to control for confounding variables. This can result in conclusions that appear scientifically valid on the surface but do not hold up under scrutiny. It’s crucial to evaluate both the methodology and the results before accepting any scientific claims.
