Suppose that different amounts of fertilizer had been used in different fields that were involved in trials of different types of wheat seeds. (a) Explain how the use of different amounts of fertilizer confounds the experimental analysis in the absence of randomization. (b) Considering the regression models with explanatory variables, if the amount of fertilizer were known, how could an analyst adjust for this confounding effect? (a) Choose the correct answer below. O A. Seed variety is highly correlated with fertilizer use. O B. Yield is uncorrelated with fertilizer use. OC. Differences in yield could be due to fertilizer rather than seed variety. O D. Fertilizer use is not uniform for each type of seed. (b) Choose the correct answer below. O A. Add a quantitative explanatory variable for the amount of fertilizer used. O B. Add a categorical explanatory variable for whether fertilizer was used. OC. Add a quantitative explanatory variable for whether fertilizer was used. O D. Add a categorical explanatory variable for the amount of fertilizer used.

Suppose that different amounts of fertilizer had been used in different fields that were involved in trials of different types of wheat seeds. (a) Explain how the use of different amounts of fertilizer confounds the experimental analysis in the absence of randomization. (b) Considering the regression models with explanatory variables, if the amount of fertilizer were known, how could an analyst adjust for this confounding effect? (a) Choose the correct answer below. O A. Seed variety is highly correlated with fertilizer use. O B. Yield is uncorrelated with fertilizer use. OC. Differences in yield could be due to fertilizer rather than seed variety. O D. Fertilizer use is not uniform for each type of seed. (b) Choose the correct answer below. O A. Add a quantitative explanatory variable for the amount of fertilizer used. O B. Add a categorical explanatory variable for whether fertilizer was used. OC. Add a quantitative explanatory variable for whether fertilizer was used. O D. Add a categorical explanatory variable for the amount of fertilizer used.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Q: Why would researchers believe that an ordinary least squares regression is superior to a partial…

A: Ordinary least square regression is a method for obtaining a linear relationship between any…

Q: An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising…

A: A regression line equation is in the form y = a + bx where b is the slope and a is the y-intercept.…

Q: P.v.n.g

A: To find the explained variation, unexplained variation, and prediction interval for an overhead…

Q: A researcher wants to test a new memory performance supplement that has shown some promise in…

A: In a 22 factorial design with different participants in each cell, the subjects under study are…

Q: A researcher studying psychological well-being between those with depression, anxiety, or mood…

A: One-factor ANOVA model: In one factor ANOVA model only one factor is studied, that is only the…

Q: A consumer buying cooperative tested the effective heating area of 20 different electric space…

A: The question is about correlation and regression Given : To find : a ) Value of correlation…

Q: A researcher notes that there seems to be a difference in the prevalence of high cholesterol among…

A: Given, A researcher notes that there seems to be a difference in the prevalence of high cholesterol…

Q: In a study examining the effects of alcohol on reaction time,Liguori and Robinson (2001) found that…

A: Introduction: Denote μ as the true mean reaction time under the influence of alcohol. As it is of…

Q: Using 20 observations, the multiple regression model y = Bo + B1x1 + B2x2 + ɛ was estimated. A…

A: Hypothesis, Ho1: the predictor variable X1 is jointly significant. H11: the predictor variable X1 is…

Q: Question 2 You are interested in whether smoking potentially influences birth weight of babies.…

A: According to the answering guidelines, we can answer only three subparts of a question and the rest…

Q: Identifying individuals with a high risk of Alzheimer’s disease usually involves a long series of…

A: As we know that the coefficient of determination explain the variability in y which is explained by…

Q: Identify which of the following studies should be tested using two-way ANOVA, bivariate correlation,…

A: Introduction: It is required to identify the studies for which two-way ANOVA, bivariate correlation,…

Q: The accompanying table lists systolic blood pressures (mm Hg) and diastolic blood pressures (mm Hg)…

A: The accompanying table lists systolic blood pressure and diastolic blood pressure of adult…

Q: You are designing a two-arm parallel-groups trial of a new blood pressure-lowering medication…

A: A two-arm parallel-groups design is applied to test a new blood pressure-lowering medication…

Q: I have a research project in statistics and I have to specify which test statistics to use. My…

A: A statistical hypothesis is an assumption or a statement about the population parameter. Hypothesis…

Q: Suppose a new policy was implemented in the state of Ohio in 2007 that greatly reduced the cost of…

A: Step 1: Step 2:=6.59-3.77-(3.44-3.12)=2.5

Q: The same media consultants decided to continue their investigation of the focal relationship between…

A: In this question, the statistical summary about three models represented by three equation has given…

Q: Question 2 The ANOVA test is O only appropriate if both variables are categorical. O sensitive to…

A: Solution

Q: 2. Consider the following two periods panel data model: Wage it = Bo + do D2 + ß₁Educit + ß₂Expit +…

A: This panel data analysis involves a two-period model that examines the factors influencing wages ()…

Q: A professor at the University of Alabama was interested in evaluating the relationship between…

A: The relationship fit to a set of experimental data is characterized by a prediction equation called…

Q: significant

Q: What are the assumptions of simple linear regression (and as a consequence the pearson’s r…

A: We find the assumption for linear regression.

Q: A Poisson regression was used to investigate how religious service attendance, expectations for the…

A: From the given information, a Poisson regression was used to investigate how religious service…

Q: Is this coefficient estimatimate on FemaleStudent statistically significant at the 1% level?…

A: The regression equation is : y= ax +by +cxy Student performance=-0.50Female professor-0.15Female…

Q: The same media consultants decided to continue their investigation of the focal relationship between…

A: Note:Hey there! Thank you for posting the question. On reading the question, it appears that the…

Q: Table 10-12. Hypothetical Study Comparing Performance of Children with Communication Disorders (CD),…

A: Descriptive statistics: The mean and standard deviation of children with CD using new method are…

Q: A researcher wants to test a new memory performance supplement that has shown some promise in…

A: Given information: α=0.01Power=0.80β=1-Power=1-0.80=0.20Estimated effect size μ2=0.24

Concept explainers

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.

Question

Suppose that different amounts of fertilizer had been used in different fields that were involved in trials of different types of wheat seeds.
(a) Explain how the use of different amounts of fertilizer confounds the experimental analysis in the absence of randomization.
(b) Considering the regression models with explanatory variables, if the amount of fertilizer were known, how could an analyst adjust for this confounding effect?
(a) Choose the correct answer below.
O A. Seed variety is highly correlated with fertilizer use.
O B. Yield is uncorrelated with fertilizer use.
O C. Differences in yield could be due to fertilizer rather than seed variety.
O D. Fertilizer use is not uniform for each type of seed.
(b) Choose the correct answer below.
O A. Add a quantitative explanatory variable for the amount of fertilizer used.
O B. Add a categorical explanatory variable for whether fertilizer was used.
OC. Add a quantitative explanatory variable for whether fertilizer was used.
O D. Add a categorical explanatory variable for the amount of fertilizer used.

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Step 1

VIEW

Step 2

VIEW

Trending now

This is a popular solution!

Step by step

Solved in 2 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

$Correlation, Regression, and Association$

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.

Similar questions

A clinical trial for a psychological therapy for trauma takes 37 women and gives them one treatment for trauma and then, a year later, gives them a different treatment. The measure used to indicate success is a Likert scale where 5 means 'l found the treatment very helpful' and 1 means 'l didn't find it helpful at all. The lead researcher gathers the data and she finds a very high variance of scores across the women in each treatment, and considers giving up the analysis. She plans to do a difference in means analysis with unequal variances (she tested and found the variances were unequal). She asks for your advice: a. She is being too hasty because she is using the wrong technique. This is a paired sample and when she takes the difference in the Likert scale for each subject across the two treatments the variance of the remaining lifferences might be so low that she can detect which treatment is statistically better b. She cannot give different treatments to the same people - it…
Maternal smoking during pregnancy can result in both pregnancy complications and reduced size of the fetus and neonate. Among women who smoke, genetic susceptibility to tobacco smoke also is a likely causative factor in adverse pregnancy outcomes. A prospective cohort study was conducted among 460 pregnant women who delivered singletons in Sapporo, Japan, from 2002 to 2005. Multiple linear regression models were used to estimate associations of maternal smoking and polymorphisms in two genes encoding N-nitrosamine-metabolizing enzymes-NQO1 and CYP2E2-with birth size. (Sasaki et al., 2008). Why was the use of multiple linear regression appropriate?
Suppose we have two SRSS from two distinct populations and the samples are independent. We measure the same variable for both samples. Suppose both populations of the values of these variables are normally distributed but the means and standard deviations are unknown. For purposes of comparing the two means, we use (a) Two-sample t procedures (b) Matched pairs t procedures (c) z procedures (d) The least-squares regression line (e) None of the above. The answer is
What variables do Teczar find have the most significant controlled associations with women in national parliaments?
a. b. C. Name: 3. You have been provided the following regression summery output for the demand for Good X. F df Significance F 0.00000798529 53.29202 Regression Residual Total Intercept Price (Px) Income (1) Price Other (Py) 3 56 59 Coefficients 355.8130 -4.9835 0.8762 -1.4893 SS 824.897 209.662 1,034.559 Standard Error 0.632473 0.939474 0.487969 0.968633 MS 255.3953 4.792375 P-value 6.45E-05 0.001985 0.078924 0.027889 Using the estimates above, state the demand function rounded to two decimals (Format: Qx=do+a1 Px + a ₂1+ a 3Py): Is the product called X a normal or inferior good? (motivate) Is the "Price Other (Py)" referring to a complement or substitute good (motivate)
A clinical psychologist wants to compare the efficacy of medication versus Cognitive Behavioral Therapy. He specifically believes that medication will reduce the frequency of suicidal ideation more than Cognitive Behavioral Therapy. He finds that the medicated group (n = 22) reports an average of 1.84 suicidal thoughts, with a sample variance = 9.01. The CBT group (n = 22) reports an average of 3.92 with a sample variance of 9.13. What would be the test statisitc the clinican observes given this data? (Be sure to round your answer to the second decimal place). "
A psychologist is conducting a two sample (independent samples) t-test to compare two treatment conditions. She intended to see whether there is a significant difference between two treatments. Following data were obtained: Treatment one group: # of participants = 20, sample mean = 75, sample standard dev (s) = 3.15. Observations are normally distributed Treatment two group: # of participants = 15, sample mean = 72, sample standard dev (s) = 3. 54. Observations are normally distributed Use 1% significance level. Assume µ1 and µ2 are the population means for groups of treatment one and two respectively. a) What is null and alternative hypotheses? b) What is the value of the test statistic? c) What is the p-value? d) What is your conclusion?
A new method was developed to reduce variability of test scores by eliminating lower scores. Two groups, one called the control group and the other, the experimental group, both took the same test. The experimental group was taught using the new method. Do the data provide sufficient evidence to conclude that there is less variation among scores when the new method is used? Perform an F-test at the 1% significance level. (Note: s, = 6.3 and Control Experimental 30 19 29 26 33 36 29 18 33 31 S2 = 3.3.) 33 18 19 32 27 32 29 30 33 ... .. First find the null and alternative hypotheses. Which of the following correctly states the hypotheses? O A. Ho: 01 72 Ha: 01 = 02 O B. Ho: 01 >02 Ha: 0102 Ha: 01 #02 O E. Ho: 01 =02 Ha: 01 02 nts SCO Compute the test statistic F. Scor (Round to three decimal places as needed.) ess
Select all statements that are true of the least-squares regression line. ) It assumes a linear relationship between the explanatory and the response variable. R-squared is the portion of sample variance in the explanatory variable that can be explained by variation in the response variable. ) It can be used to predict the mean response of the explanatory variable. | R-squared is the portion of sample variance in the y variable that can be explained by variation in the x variable.