Looking for an answer to the question: **Are age and gender independent variables?** On this page, we have gathered for you the most accurate and comprehensive information that will fully answer the question: **Are age and gender independent variables?**

The dependent variable is the outcome, in this case heart disease. The independent variables are blood pressure, smoking status, and dietary intake. Individually, blood pressure, smoking status, and dietary intake provide information about heart disease.

One may also ask, what type of variable is gender in statistics? A variable is said to be Binary or Dichotomous, when there are only two possible levels. These variables can usually be phrased in a “yes/no” question. Gender is an example of a binary variable.

Independent variables are what we expect will influence dependent variables. A Dependent variable is what happens as a result of the independent variable. For example, if we want to explore whether high concentrations of vehicle exhaust impact incidence of asthma in children, vehicle exhaust is...

A nominal variable has no intrinsic ordering to its categories. For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to the categories. Read everything about it here. Besides, is gender nominal or ordinal?

Age is frequently collected as ratio data, but can also be collected as ordinal data. This happens on surveys when they ask, “What age group do you fall in?” There, you wouldn't have data on your respondent's individual ages – you'd only know how many were between 18-24, 25-34, etc.

A great example of this is a variable like age. Age is, technically, continuous and ratio. A person's age does, after all, have a meaningful zero point (birth) and is continuous if you measure it precisely enough.

Age can be both nominal and ordinal data depending on the question types. I.e "How old are you" is used to collect nominal data while "Are you the firstborn or What position are you in your family" is used to collect ordinal data.

An independent variable is used in statistics to predict or explain a dependent variable. For example, Age and Gender might be used as independent variables to predict the age of death or life expectancy (dependent variables).

In the present view, it is not because age is an independent variable which is not subject to experimental manipulation, but rather because it is not an independent variable at all.

Examples of categorical variables are race, sex, age group, and educational level. While the latter two variables may also be considered in a numerical manner by using exact values for age and highest grade completed, it is often more informative to categorize such variables into a relatively small number of groups.

If one wants to estimate the cost of living of an individual, then the factors such as salary, age, marital status, etc. are independent variables, while the cost of living of a person is highly dependent on such factors. Therefore, they are designated as the dependent variable.

categorical variable A nominal variable has no intrinsic ordering to its categories. For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to the categories.

Independent variable causes an effect on the dependent variable. Example: How long you sleep (independent variable) affects your test score (dependent variable). This makes sense, but: Example: Your test score affects how long you sleep.

The type of therapy given is the explanatory variable; it may or may not affect the response variable. In this example, we have only one explanatory variable: type of treatment. In real life you would have several more explanatory variables, including: age, health, weight and other lifestyle factors.

In our medical example, age is an example of a quantitative variable because it can take on multiple numerical values. It also makes sense to think about it in numerical form; that is, a person can be 18 years old or 80 years old.

Age can be both nominal and ordinal data depending on the question types. I.e "How old are you" is used to collect nominal data while "Are you the firstborn or What position are you in your family" is used to collect ordinal data. Age becomes ordinal data when there's some sort of order to it.

Gender and race are the two other categorical variables in our medical records example. Quantitative variables take numerical values and represent some kind of measurement. In our medical example, age is an example of a quantitative variable because it can take on multiple numerical values.

Age can be both nominal and ordinal data depending on the question types. I.e "How old are you" is used to collect nominal data while "Are you the firstborn or What position are you in your family" is used to collect ordinal data. Age becomes ordinal data when there's some sort of order to it.

Dichotomous variables are nominal variables which have only two categories or levels. For example, if we were looking at gender, we would most probably categorize somebody as either "male" or "female". This is an example of a dichotomous variable (and also a nominal variable).

It is a variable that stands alone and isn't changed by the other variables you are trying to measure. For example, someone's age might be an independent variable. Other factors (such as what they eat, how much they go to school, how much television they watch) aren't going to change a person's age.

Age can be both nominal and ordinal data depending on the question types. I.e “How old are you” is a used to collect nominal data while “Are you the first born or What position are you in your family” is used to collect ordinal data. Age becomes ordinal data when there's some sort of order to it.

You can tell if two random variables are independent by looking at their individual probabilities. If those probabilities don't change when the events meet, then those variables are independent. Another way of saying this is that if the two variables are correlated, then they are not independent.

These changing quantities are called 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 you Identify Independent and Dependent Variables? The easiest way to identify which variable in your experiment is the Independent Variable (IV) and which one is the Dependent Variable (DV) is by putting both the variables in the sentence below in a way that makes sense. “The IV causes a change in the DV.

Olivier ⭐ Answeregy Expert

Significance of the Independent Variables Q Dependent Variables Independent Variables Significance at the 0.05 level (2-tailed) Gender Age 1 I find online education mechanical due to its dependency on technology. r -.242 -.314 s .008 .001 2 I prefer attending face-to-face classes. r -.185 -.293 s .045 .001

Gabe ⭐ Answeregy Expert

Answer: An independent variable is exactly what it sounds like. It is a variable that stands alone and isn't changed by the other variables you are trying to measure. For example, someone's age might be an independent variable. Other factors (such as what they eat, how much they go to school, how much television they watch) aren't going to ...

Gail ⭐ Answeregy Expert

Some commonly used independent variables in medical and social research include race, gender, education level, and age. For an example, let’s consider a study relating heart disease to blood pressure, smoking status, and dietary intake.

Martin ⭐ Answeregy Expert

Dependent and Independent Variables. In analytical health research there are generally two types of variables. Independent variables are what we expect will influence dependent variables. A Dependent variable is what happens as a result of the independent variable. For example, if we want to explore whether high concentrations of vehicle exhaust impact incidence of asthma in …

Summer ⭐ Answeregy Expert

These variables have minimum two divisions such as Male/Female, Yes/No. This scale has no numerical value, for example – gender, ethnicity, race etc. Also, what type of variable is age? continuous . Thereof, what type of variable is gender in statistics? A variable is said to

Case ⭐ Answeregy Expert

independent variable determine the values of the dependent variable. The independent variable ... (extraneous variable). She can then use these age data to control for the uninteresting effect of ... A class collected data on each student’s favorite subject and gender. 20. A student collected data on daily rainfall and daily average temperature.

Alpha ⭐ Answeregy Expert

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Wendy ⭐ Answeregy Expert

However, gender cannot be imposed or changed by investigators, so it is always an attribute independent variable, when men and women are compared in the study (i.e., when it is an independent variable). .

Benicio ⭐ Answeregy Expert

The dependent variable (sometimes known as the responding variable) is what is being studied and measured in the experiment. It's what changes as a result of the changes to the independent variable. An example of a dependent variable is how tall you are at different ages. The dependent variable (height) depends on the independent variable (age).

Michell ⭐ Answeregy Expert

A state-of-the-art alternative would be to conduct novometric analysis using all of the independent variables and the control variables as potential predictors, however the software required for ...

Homer ⭐ Answeregy Expert

As demographic variables are typically fixed (e.g. age/gender) and this is the required quality for independent variables however, this would be suitable for non-experimental design research.

Franklin ⭐ Answeregy Expert

Although social class, religion, gender, ethnicity and age are often treated as independent variables (e.g., factors, forces, structures) and invoked as causal explanations for various outcomes, this paper approaches these constructs in more distinctive, humanly-engaged terms. Rather than representing forces that almost mysteriously impose themselves on people, …

Samer ⭐ Answeregy Expert

Although participant-related demographics such as participant’s gender, age, income, and race serve as control variables for most studies, other attitudinal measures, such as social conservatism, party affiliation, political ideology, media habits, issue salience, and motivation to control prejudice, are also measured (Dixon, 2006b, 2007; Dixon & Azocar, 2007; Mastro & …

Erwin ⭐ Answeregy Expert

An Example: Age A great example of this is a variable like age. Age is, technically, continuous and ratio. A person's age does, after all, have a meaningful zero point (birth) and is continuous if you measure it precisely enough. It is meaningful to say that someone (or something) is 7.28 year old.

Elizabeth ⭐ Answeregy Expert

Apart from testing bivariate gender differences, we also test a multivariate model predicting career level, using the following independent variables: performance (publications; field normalized citation score), academic age (see …

Jeanette ⭐ Answeregy Expert

For example, Age and Gender might be used as independent variables to predict the age of death or life expectancy (dependent variables). In experimental designs, the independent variables are manipulated by the researcher (e.g., different dosages of a drug).

Jewel ⭐ Answeregy Expert

Another way of looking at the data is defining the dependent and independent variables: Dependent variable is the variable of interest. Independent variable is the grouping variable. Let us say, you want to find out if HbA1c differ by gender or ethnicity. Then HbA1c is the dependent variable, and gender and ethnicity are independent variables.

Keith ⭐ Answeregy Expert

Independent variables or correlates of happiness included race (Black or White), age (< 65 vs. 65 and older), gender (male vs. female), perceived income (sufficient vs. insufficient to meet basic needs), health literacy (adequate vs. inadequate), and self-rated health (excellent/very good/good vs. …

Philip ⭐ Answeregy Expert

The three independent variables are: age, gender and Academic performance. In varying degrees, all of the independent variables, were reported in the literature as having positive correlations with depression. Rationale of the study The purpose of this study was to find out age and gender difference in depression and academic performance with ...

Audrey ⭐ Answeregy Expert

variable i.e., Age and gender and independent variables i.e., Current CGPA and Academic workload and dependent variable like how much a person cheat. Because Cronbach's Alpha value is negative, therefore we may conclude that all of the question variables are not reliable. Age, current CGPA, Gender, Missing deadlines are reliable questions/variable hence will provide …

Audrey ⭐ Answeregy Expert

of juveniles, gender, living conditions, and, attendance at school. The effects of these variables have been documented in past and present research. These studies focused on these different variables in an attempt to clarify and simplify the research on the commitment rate of juveniles.

Wayne ⭐ Answeregy Expert

These hypotheses have the dependent variable that homosexuals should have the right to marry one another. The three independent variables are age, gender and religion. The independent variables are the major reasons of having a division in opinions on the topic of homosexuality.

Catalina ⭐ Answeregy Expert

I have two variables age and type of car bought. Age is in groups. Eg. $<25$, $26-35$, $36-45$, $46-55$, $>55$. Car is 1. American, 2. Japanese, 3. European. It seems like a simple Chi Square to test relationship, but there is more than 2 categories? Does this mean I have to use a One Anova test? How can I do this without a continuous variable?

Eugene ⭐ Answeregy Expert

To control for educational differences and to determine the potential effects of age and gender differences on the dependent variables (i.e., perseverative, nonperseverative, and random errors), subjects were stratified by age, 54 to 69 and 70 to 89 years, and a 2 × 2 (Age × Gender) multivariate analysis of covariance (MANCOVA), using education as the covariate, was …

Rohan ⭐ Answeregy Expert

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Jamie ⭐ Answeregy Expert

Table 2 is a pivot table displaying the age and gender of the incoming freshman class at a public university. Using the information in the table, test whether gender and age are independent variables. Your test should involve comparing two probabilities. Report the probabilities and what this means about whether or not the variables are related.

Felton ⭐ Answeregy Expert

Independent variables were age (79 years or less and 80 years or older) and gender (women and men). Using of Pillai’s criterion, the combined dependent variables were significantly affected by both age (F4, 996 = 115.33, ) and gender (F4, 996 = 5.87, ), …

Garry ⭐ Answeregy Expert

Age is a key demographic variable, frequently recorded in survey data as part of a broader set of demographic variables such as education, income, race, ethnicity, and gender. These help to identify representativeness of a particular sample as well as describing participants and providing valuable information to aid analysis.

Regina ⭐ Answeregy Expert

A linear model was constructed for each health status group. In these models, the dependent variable was eGFR and the independent variables were age, gender, and interaction of age and gender. These models were used to calculate the gender-specific rates of decline of eGFR and to test gender-specific differences.

Faye ⭐ Answeregy Expert

Sociologists increasingly may be attending to matters of agency and social process, but at the same time, concepts such as social class, religion, gender, ethnicity, and age are often treated as independent variables (e.g., factors, structures, or forces) and are commonly and centrally invoked as causal explanations for human experiences that are framed as dependent variables.1 By …

Alison ⭐ Answeregy Expert

As a result, the influence of the independent variable in the presence of the moderator variable. Gender; Race; Class; Suppose you want to conduct a study, educational awareness of a specific area. Educational awareness will be your dependent variable. The area will be an independent variable if you feel that the student’s age/race may also ...

Terry ⭐ Answeregy Expert

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Zakary ⭐ Answeregy Expert

In a factorial design, a(n) _____ between independent variables indicates that the effect of one independent variable is different at different levels of the other independent variable. ... Gender and age are examples of _____ variables. participant attribute subject ALL OF THE ABOVE.

Clyde ⭐ Answeregy Expert

CATEGORICAL VARIABLES: variables such as gender with limited values. They can be further ... CONTINUOUS (SCALE) VARIABLES: Measurements on a proper scale such as age, height etc. INDEPENDENT VARIABLE: The variable we think has an effect on the dependent variable. ... independent variable is the group the subject is in which is categorical.

Edwin ⭐ Answeregy Expert

Double-click on variable MileMinDur to move it to the Dependent List area. Click on variable Athlete and use the second arrow button to move it to the Independent List box. Click Next directly above the Independent List area. The heading for that section should now say Layer 2 of 2. Click on variable Gender and move it to the Independent List box.

Serenity ⭐ Answeregy Expert

– Independent variables: age (years), gender (male/female), race/ethnicity (Black, White, Asian, or Hispanic), frequency of going out to eat (5+ times/week vs less than 5 times/week) Linear Regression Assumptions • Linear regression is a parametric method and

Angeles ⭐ Answeregy Expert

Further, the study involved an examination of the extent to which the independent variables were predictors of academic achievement in the English Composition I class. Results of a Pearson product-moment correlation test showed race/ethnicity, gender, and age were correlated with ENC1101 grades.

Paralee ⭐ Answeregy Expert

manipulating two or more independent variables in a single experiment. A researcher designs an experiment by manipulating the weight of an individual (normal, over); age (young, middle, old); and gender (male, female).

Kandy ⭐ Answeregy Expert

So, I have this dataset with a hormonal measure as independent variable and behavioral measures as dependent variables. I am using a linear regression as my model and after a backward selection, ended up with 4 significant dependent variables. However, I forget to include in it the age and sex of individuals.

Juanita ⭐ Answeregy Expert

which implies that these three independent variables are important predictors of job satisfaction. Ho 2: - There is no significant relative contribution of each of the independent variables (age, marital status and educational background) on dependent variable (Job Satisfaction)

Kemar ⭐ Answeregy Expert

For example, using the hsb2 data file we will look at writing scores (write) as the dependent variable and gender (female) and socio-economic status (ses) as independent variables, and we will include an interaction of female by ses. Note that in SPSS, you do not need to have the interaction term(s) in your data set.

Damon ⭐ Answeregy Expert

consumpt ion at age 30 and gender (independent variables) with probability of developing liver cancer during a 10 year period (dependent variable). Liver cancer is a categorical variable with two categories at the end of the follow-up period: “cancer” ...

Armani ⭐ Answeregy Expert

SPSS software was used to analyze and compare the variables. A) Perform various exploratory analyses (graphical/numerical) to assess: the distribution of BMI by GENDER, AGE, and RESTAURANT. B) Fit a multiple linear with BMI as your dependent variable and GENDER, AGE, and RESTAURANT as the independent variables.

Charlie ⭐ Answeregy Expert

The Independent Effect of Each Independent Variable. In a sense, the equation above is a prediction of what an individual's BMI will be based on their diet score, gender and age group. The equation has an intercept of 18.0, meaning that I start with a baseline value of 18.

Lynette ⭐ Answeregy Expert

Methods: We developed a mixed-effects model to examine weight after gastric bypass surgery while controlling for several independent variables: gender, anastomotic technique, age, race, initial weight, height, and institution. We contrasted this approach with traditional uncontrolled analyses using percent excess weight loss (%EWL).

Reginald ⭐ Answeregy Expert

Age is a key demographic variable, frequently recorded in survey data as part of a broader set of demographic variables such as education, income, race, ethnicity, and gender. These help to identify representativeness of a particular sample, as well as describing participants and providing valuable information to aid analysis.

Norberto ⭐ Answeregy Expert

The Age Variable in Psychological Research l Joachim F. Wohlwill Clark University The chronological age of the individual has generally represented one of the most popular independent variables used in child development research and is included with some frequency even in research of a general experi mental nature.

Caryl ⭐ Answeregy Expert

A researcher can also use more than two independent variables, and this is an n-way ANOVA (with n being the number of independent variables you have). For example, potential differences in IQ scores can be examined by Country, Gender, Age group, Ethnicity, etc, simultaneously.

Karen ⭐ Answeregy Expert

2) The independent variable, age , which is the participant's age in years; 3) The independent variable, weight , which is the participant's weight (technically, it is their 'mass’); 4) The independent variable, gender , which has two categories: "Male" and "Female"; 5) The independent variable, VO2max , which is the maximal aerobic capacity.

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