The third variable could be one which is correlated to both variables. These are called confounding variable.
For example, in the UK you could find a correlation between coastal air pollution and ice cream sales. This is not because eating ice cream causes air pollution nor because air pollution causes people to eat ice cream. The confounding variable is the temperature. Warm weather gets people to drive to the sea!
basketball and football
That depends on what you want to know, the form of the answer, how and where the survey is to be conducted and lots of other variables. Once you have all of that sorted, the best and simplest method is to consult tables or software.
The population is every data point you intend to generalise the survey results to. The sample frame is those data points that you can pick from for the survey. The sample is which of these data points you actually survey, and the sample size is how many of those data points there are. For instance, if you have 700 students in a school, and you have access to 300 of them, and decide to give 30 of them a survey, the sample size is 30.
Correlation only shows how well two variables vary together; it does not show the causation of the effect - there is often a third factor (or variable) which causes both, or causes one and influences the other.An example:A survey of all the inhabitants in a village found a strong (but not perfect) correlation between foot (shoe) size and mathematical ability - the larger the foot size the better they were at mathematics. Does this mean that foot size causes the mathematical ability of someone?In this case no; there is a third factor which causes the first (foot size) and has some influence over the second (mathematical ability): the survey was of all the inhabitants of the village which includes babies and young children.The third factor here (the real cause of the "apparent" correlation) is the age of the inhabitant: the older someone gets (from being a baby to a teenager) the larger their foot size will become, but also the better their mathematical ability is (likely) to get. The babies with the smaller feet will have very limited mathematical ability, the 7 year olds with larger feet will have better mathematical ability, the teenagers with even larger feet will have better mathematical ability again. The correlation need not be perfect as there will be older people with less mathematical ability, but "on average" (sic) the older someone is the better their mathematical ability (along with the larger their feet).
Data compilation is taking survey or evaluation answers, gathering them into a database, and analyzing the results for further suggestions, improvements, and/or recommendations.
Yes, a survey typically includes variables that are measured or observed, such as demographics, opinions, behaviors, or attitudes. These variables help researchers analyze and interpret the data collected from the survey.
Survey results refer to the data and feedback collected from a survey conducted among a group of individuals. These results typically include statistics, trends, and insights that summarize the responses to the survey questions. Survey results are used to analyze opinions, behaviors, preferences, and other relevant information from the surveyed group.
A control in a survey is a group or factor that is used as a standard of comparison to evaluate the effect of changes in other variables being studied. Controls are essential for research validity as they help to isolate and measure the impact of specific factors under investigation. By holding certain variables constant, researchers can better understand causality and ensure accurate results.
You can find the results of a customer satisfaction survey you have taken part in by contacting the company which provided the survey. Sometimes you can also find the results posted online.
Descriptive surveys allow researchers to collect data on a wide range of variables in a structured way. They provide a snapshot of a population's characteristics or opinions at a specific point in time. The results can help identify patterns, trends, and relationships between variables.
affect the results of the survey.
The time it takes to get results from a seismic survey can vary depending on the size and complexity of the survey. Generally, it can take anywhere from a few weeks to a few months to process and interpret the data collected during the survey.
The answer depends on what information the survey collects.
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A sample survey is quicker and cheaper. If the survey is well designed then the results are likely to be close to their true values.
Correlational surveys involve measuring the relationship between two or more variables without manipulating them. By collecting data on these variables from a sample of participants, researchers can determine the extent to which changes in one variable are associated with changes in another, providing insight into potential patterns or connections between the variables.
Data analysis must be used to understand the results of a survey. Otherwise, the data collected by the survey would remain a jumbled collection of data.