It is a numerical coefficient whose does not change as the variables change.
If the product of two variables is equal to a constant, then they are inversely proportional. eg. If xy=c where c is a constant, then x and y are inversely proportional.
Every time the independent variables change, the dependent variables change.Dependent variables cannot change if the independent variables didn't change.
control variables: the things that are not changing.Independent variables: the things that you change.Dependent variables: the things that are changed due to the independent variable
Yes, if you have two limiting variables with other possibles variables between them, the variables between the limiting variables would be continuous.
characteristics of imeperative languages 1. variables 2.assignment 3.sequecing
It is a numerical coefficient whose does not change as the variables change.
The three demographic variables commonly used are age, gender, and income. These variables help categorize and identify characteristics of a population for research and marketing purposes.
Qualitative variables are variables that are used to categorize data based on characteristics or qualities, such as color, gender, or type of vehicle. They are non-numeric and are used to label or describe observations rather than measure them.
Behavioral variables are the criteria or yardsticks for measuring and comparing among different individuals. The are mainly observable and measurable characteristics or responses. Agorua, Christopher Eme-eji
You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.
Variables in a questionnaire are characteristics or attributes that can be measured or evaluated, such as age, gender, income level, or satisfaction score. These variables help researchers gather data and analyze relationships between different factors in a study. They provide a way to quantify and categorize information obtained from survey respondents.
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Characteristics in a study refer to the distinctive features or attributes of a particular group, subject, or phenomenon being examined. These characteristics help researchers define and categorize the subjects, variables, or elements of interest in their study. Understanding the characteristics of a study population or sample is essential for drawing meaningful conclusions and generalizing findings.
A participant variable is a characteristic or trait of the individuals taking part in a research study that may influence the outcomes being measured. These variables are important to consider because they can impact the results and interpretation of the study findings. Researchers often need to control for participant variables to ensure the validity and reliability of their results.
A situational variable is a factor that can influence behavior in a specific situation. These variables can include environmental factors, social norms, or specific circumstances that impact how individuals act or respond in different situations. Understanding situational variables is important in psychology and sociology to predict and explain behavior.
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.