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When there are no identifiable trends in a graph it most likely means that there is no relationship between the two variables?
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∙ 12y ago
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∙ 12y ago
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What does it most likely mean if a graph shows no identifiable trends?
No Solution!
Two variables that are likely to be correlated?
Height and Weight.
What are the two types of variables and how do they differ?
The two types of variables are: independent variables and dependent variables.Independent variables are variables (ideally only one or very few per experiment) that the experimenter manipulates in the experiment. For example, if you were testing the effect of temperature on plant growth rates, you would likely have similar plants in similar conditions but in areas with different temperatures. The experimenter is changing the temperature between the groups of plants, so the temperature would be the independent variable.The dependent variables are the effects the independent variable has on the experimental subjects. They are changes not being directly controlled or manipulated by the experimenter. In the above temperature vs. plant growth example, the rate of plant growth would be the dependent variable; it depends on the temperature.
What is definning variables?
A variable is any factor, trait, or condition that can exist in differing amounts or types. An experiment usually has three kinds of variables: independent, dependent, and controlled.
How can there be a correlation between two things even though one does not cause the other?
Let's say we look at the consumption of junk food and heart attacks. What we would see is a correlation. The more junk food you eat the less risk of a heart attack. There is a correlation but is there a cause and effect relationship? Probably not. Young people eat a lot more junk food than older people. And older people are much more likely to suffer from a heart attack. Mathematically this is due to correlation between your x variables. In statistical analysis you usually assume independent variables. In reality thins are much more complicated. If you want to establish true relationships you need to use design of experiments (DoE).
What is the relationship between algae and minnow?
Algae provide food and oxygen for minnows through photosynthesis, while minnows help control algae populations by consuming them. This mutual relationship helps maintain a balance in aquatic ecosystems.
In a research study is one variable is changed to see how it affects behavior the study is most likely an?
experimental study. In experimental studies, researchers manipulate an independent variable to observe its effect on a dependent variable while controlling for other variables. This allows for making causal inferences about the relationship between the variables.
What does it most likely mean if a graph shows no identifiable trends?
No Solution!
Which observation would most likely be made before an experiment?
Before an experiment, an observation might involve noticing a pattern or trend in data, identifying a potential relationship between variables, or recognizing a need for further investigation based on existing information.
What is bubblegum romance?
This type of relationship is likely to be between young people and is likely to be platonic and, metaphorically speaking, sweet.
In the drop and bounce lab characterized the relationship of variables in the experiment?
The drop and bounce lab likely investigated how the drop height of an object relates to the height of the bounce. This relationship can be characterized by analyzing how changes in drop height impact the rebound height of the object. By recording and analyzing these data points, researchers can determine if there is a linear, quadratic, or other relationship between the drop height and bounce height.
Is there a relationship between employee satisfaction and absenteeism?
There is a definite relationship between employee satisfaction and absenteeism. Employees who are happy on the job will be more likely to show up to work. Conversely, employees who are dissatisfied with their jobs will be less likely to come in.
The graph at the top of the second column of page 122 shows a condition in which there is what?
The graph likely shows a relationship between two variables, such as temperature and precipitation. It could illustrate a specific condition, like a drought or a heatwave, depending on the data being represented in the graph.
Provide an example of a prediction or modelling, based on relationship between two variables employed in the media presented in a misleading way. This will be a chart or table1)What's the apparent message2)What would the clear, accurate message be?
An example of a prediction or model that is presented in a misleading way in the media is a chart or table that shows a strong correlation between two variables, but fails to mention other factors that may be influencing the relationship. The apparent message of this chart or table might be that there is a direct and causal relationship between the two variables, and that changes in one variable will always result in corresponding changes in the other. For example, a chart might show that there is a strong correlation between the amount of time that people spend on social media and their levels of anxiety and depression. The apparent message of this chart might be that social media use directly causes anxiety and depression. However, the clear and accurate message of this chart would be that there is a complex relationship between the two variables, and that other factors may also be influencing the relationship. For example, it is possible that people who are already anxious or depressed are more likely to spend more time on social media, rather than the other way around. The accurate message would be that more research is needed to understand the relationship between social media use and mental health, and that the apparent correlation in the chart does not necessarily indicate a causal relationship.
How do you determine whether a relationship shown in a table is a proportional relationship?
A proportional relationship is of the form y = kx where k is a constant. This can be rearranged to give: y = kx → k = y/x If the relationship in a table between to variables is a proportional one, then divide the elements of one column by the corresponding elements of the other column; if the result of each division is the same value, then the data is in a proportional relationship. If the data in the table is measured data, then the data is likely to be rounded, so the divisions also need to be rounded (to the appropriate degree).
Two variables that are likely to be correlated?
Height and Weight.
Is there any relationship between size and pitch of a snare drum?
If the drum is larger, most likely that the pitch is lower.
