Plot Nutrients addec # of species 36 36 3 32 4 34 33 3 30 20 3 23 4 21 10 4 16 Avg 5.5 1.8 28.1 St. Dev 2.872281323 1.53622915 7.006425622 LO

Q: Give 2 characteristics that indicate a linear model may be appropriate to model a data set

A: In bare eyes, it is not so easy to identify or tell whether a linear model is appropriate to model a…

Q: do you need to add the days to the regression equation

A:

Q: what should you put for the output range?

A: Solution:  The procedure of performing the one way ANOVA are One way ANOVA test can be performed…

Q: d. Find the p-value and draw a Normal curve with z-statistic and appropriate shaded region. Normal…

A: The scientists observed that 10 of the 50 metal tagged penguins survived, compared to 18 of the 50…

Q: Explain in detail how regression analysis can be used to forecast the demand for a firm’s product or…

A: The literal meaning of word regression means stepping back or going back toward the average.

Q: The cost of a daily newspaper varies from city to city. However, the variation among prices remains…

A: From the provided information, Population standard deviation (σ) = 20 ¢ = $0.2 Sample mean (x̄) = 95…

Q: The quadratic model for the given data is wrong.

A: By using regression to find a quadratic model for the given data. x 0.6 0.7 2.6 4.7 5.3 y -5.6…

Q: Use Excel to develop a regression model for the Hospital Database (using the "Excel Databases.xls"…

A: The following data is given in the question. To fit a regression model, Go to Data Tab Choose Data…

Q: I asked above if you can please show the calculation using the graphing calculator, not Excel. Can…

A: It is given that maximal error (E) is 0.001 and the confidence level is 99%.

Q: make a regression analysis about any healthcare issue

A: Let's perform a simple regression analysis on a healthcare issue. We'll analyze the relationship…

Q: FOR THIS RESPONSE PLEASE USE EXCEL.  I need step-by-step calculations and formulas (formulas for…

A: Back   Side Sitting 140 141 144 144 143 145 146 145 147 141 144 148 139 136 144 Sum=710…

Q: stephanie has achieved the 45% percentile for long jump compared to 13 year old females. the mean of…

A: From the given information,Mean of the group (µ) = 66Standard deviation (σ)= 4P (X<x ) = 0.45.

Q: An automotive engineer computed a least-squares regression line for predicting the gas mileage (y)…

A: Given : y = -0.14x + 38.78

Q: Write a multiple regression equation that can be used to analyze the data for a two-factorialdesign…

A: Let x be the variable representing factor A with two levels such that                  Since factor…

Q: Write short note on regression line?

A: Introduction: Independent and dependent variables in regression: In a simple regression, the…

Q: The owner of a moving company typically has his most experienced manager predict the total number of…

A: The scatter plot for the given data set with hours on the y- axis and cubic metres on the x-axis is…

Q: KNOW HOW TO DO PERCENT ERROR EQUATION?

A: Percent error equation is used to find the percentage of error in a data.

Q: 1. The prices of Rawlston, Inc. stock (y) over a period of 12 days, the number of shares (in 100s)…

A: The sample data values are shown…

Q: Comparative static analysis involves

A: Comparative static analysis:  It is the comparison of two different economic outcomes. That means…

Q: explain  Regression analysis and its limations

A: Regression analysis  :  Regression  analisis is a power statstical method  is identifying  the…

Q: What is basic regression? What is multiple regression? How do they both relate to Data Mining?

A: Independent and dependent variables in regression: In a simple regression, the variable of interest,…

Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.