A residual plot has data points that are all very close to the x-axis. What does this say about the data?

Q: In linear regression, how can you minimise the error between predicted and actual observed values?

A: Suppose a sample of n sets of paired observations is available. These observationsare assumed to…

Q: What information does a residual plot give us?

A: A residual plot is the graph with residuals on vertical axis and independent variable on horizontal…

Q: A football coach is looking for a way to identify players that are "under weight". The coach decides…

A: Answer is  210  pounds

Q: 4. The scatter plot on the right shows the relationship between two variables, along with the…

A: Given that -

Q: What are the objects of regression?

A: Regression: Regression analysis estimates the effect that changing one independent variable has on…

Q: A football coach is looking for a way to identify players that are "under weight". The coach decides…

A: Given :  y=-51+3.2x The lowest weight possible for a 72 inch player to not be considered under…

Q: explain why the following statement is false A residual plot should show a pattern if the…

A: Residual Plot: It is the graphical representation of the residuals of a regression model. It is…

Q: Define the assumptions that inferential statistics in regression are based upon?

A: Solution: Regression is a technique that is used to estimate the dependent variable by using the one…

Q: The percent of the total variance that can be explained by the regression equation is

A: Given information: a=684.65b=7.2884r2=0.99724

Q: What kind of plot is useful for deciding whether finding a regression line for a set of data points…

A: Scatter plot: A scatter plot is a mathematical diagram which shows a relationship between two…

Q: When data is normally distributed the mean equals the mode. True

A: Normal distribution

Q: student working on a physics project investigated

A:

Q: Explain why fitting a linear model to this data may be misleading. If you fit a linear model to this…

A: Given:

Q: Explain various Assumptions of the Fixed Effects Regression ?

A: The fixed effect principle is that the independent variables are correlated with the…

Q: If the quantile-quantile plot of your data versus a normal curve is linear, the data is likely…

A: If all the observations in the quantile plot are very close to the straight line, then it can be…

Q: What proportion of the variability in the Salaries is explained by the multiple regression model…

A: The regression analysis is conducted using EXCEL. The software procedure is given below: Enter the…

Q: What level of measurement must the data be in order to perform the least squares regression…

A:

Q: The regression equation is intended to be the “best fitting” straight line for a set of data. What…

A: There can be many lines that can relate the independent and the dependent variables. But one of the…

Q: What is A REGRESSION LINE?

A: A regression line is a line which is generally used to estimate a dependent or response variable…

Q: What type of function would describe a curve that best fits the data based on the scatter plot…

A: I have given an answer in step 2.

Q: Linear regression was used to describe the trend in world population over time. Below is a plot of…

A: A residual plot is a graph that shows the residuals on the vertical axis and the independent…

Q: A measure of the amount of variation in the observed values of the response variable explained by…

A:

Q: What are the assumptions of Inferential statistics in regression?

A: Regression analysis is used to predict the dependent variable by using the one or more independent…

Q: A football coach is looking for a way to identify players that are "under weight". The coach decides…

A: Answer is  155 pounds

Q: The data table available below gives the annual cost per square foot of 50 commercial leases for…

A: A prediction interval is a range of values that predicts the value of a new observation, based on…

Q: Explain why it is not a good idea to exclude an intercept, b0 , from any linear regression model?

A: A line of regression is given as, y=b0+b1x Where,  b0 is the intercept. b1 is the slope. x is the…

Q: A football coach is looking for a way to identify players that are "under weight". The coach decides…

A: 198.24 pounds Here we are interested in finding lower confidence bound for x=67  y= -58+4(67) y= 210…

Q: What formula is used to gain information about an individual data value when the variable is…

A: Solution: 6. Let X be the random variable. From the given information, X is normally distributed.

Q: True or False: The residual of a data point is the observed value minus the predicted value.

A: Introduction: The population regression model of a response variable y on explanatory variables, x1,…

Q: What does it mean for a regression line to be the "best-fit" line.

A: The form of the simple linear regression line is given by,

Q: A football coach is looking for a way to identify players that are "under weight". The coach decides…

A: Regression equation has the form Y= a + bX, where Y is the dependent variable , X is the independent…

Q: Interpret the values of the regression coefficients (intercept and slope)in this context. Note…

A: The regression analysis is conducted using EXCEL. The software procedure is given below: Enter the…

Q: Which of these choices is true for the slope of the least-squares regression line? It is unitless.…

A: The line of regression is given as y=a+bx, where 'a' and 'b' are constants. The constant 'b' is…

Q: The PRESS statistic is a measure of how well a regression model will predict new observations. O…

A: True

Q: in multiple regression analysis, a residual is the difference between the value of a dependent…

A: We know that, In any regression model, Residual is the difference between the value of a dependent…

Q: The graph shows a bivariate data set and its least squares regression line. Draw the residual plot…

A:

Q: Looking at the following residual plot, what can you conclude

A: Residual plot analysis is critical to verification of linear regression assumption.

Q: Why the regression line is a straight line rather than a curved line?

A:

Q: Complete the statement. When all points fall on the regression line, the value of the correlation…

A: # When all points fall on the regression line, the value of the correlation coefficient is...??

Q: The fish in my pond have mean length 12 inches and mean weight 5 pounds.  The correlation…

A: In this case, weight is the dependent variable (y) and length is the independent variable (x).

Q: Give an example of how a nonrepresentative sample can severely affect a regression analysis.

A: Necessity for a representative sample:In case of observational studies, it is essential for the…

Q: Explain trend projection with regression?

A: Trend: It is a long term fluctuations in a data. It is one of the component of time series.…

Q: The double box-and-whisker plot compares the battery life (in hours) of two brands of cell phones.…

A: Here from given wisher and box plot for brand A and brand B Write 5 point summary from given two box…

Q: Explain the process of Computing the Regression Line?

A:

Q: Explain intuitively and using maths and graph why a small variation in the independent variables…

A: Small variation in the independent variable

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related. 

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.