We are interested in studying the relationship between severity of COVID 19 andeconomic growth. The severity of COVID was measured by the average no of patientsreported in year 2021 per million of population and economic growth was measured as GDPgrowth rate. A random sample of 5 counties has been chosen and the table below shows the3.information on both of the variables:County no COVID severity index GDPGrowth(%)150023003-х310014800-21000-4a)Which of the two is independent variable and which of the two is dependentvariable?b)kind (form, strength and direction) of the relationship do you observe between thesevariables? ExplainSketch the scatter plot between COVID severity and economic Growth. What

Given Information: Consider the given data: County no COVID severity Index GDP Growth 1 500 0…

Answered: 3. We are interested in studying the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Would someone familiar with SPSS be able to help with sub-question d please?
Absenteeism: Absenteeism can be a serious employment problem. It is estimated that absenteeism reduces potential output by more than 10%. Two economists launched a research project to learn more about the problem. They randomly selected 100 organizations to participate in a 1-year study. For each organization, they recorded the average number of days absent per employee and several variables thought to affect absenteeism. Question: Use the t-tests and the slope coefficient for U/M Rel to describe how the relationship between the union and the management affects absenteeism. (both MLR and t-test are provided below) Data: Wage Pct PT Pct U Av Shift U/M Rel Absent 22477 8.5 57.1 1 1 5.4 29939 1.9 41.5 0 1 4.1 22957 12.2 52.6 1 0 11.5 18888 30.8 65.1 0 1 2.1 15078 6.8 68.8 0 1 5.9 15481 5.1 46.4 0 0 12.9 21481 25.3 38.9 0 1 3.5 29687 9.2 17.2 0 0 2.6 13603 8.4 12.9 0 0 8.6 18303 4.9 18.1 0 1 2.7 20832 23.8 64.4 1 1 6.6 22325 24.1 63.7 1 1 2.1 19964 8.6…
disp hp qsec wt Use the following visualization to answer questions 2 - 4. mpg drat drat mpg qsec wt hp disp -1 -0.8 -0.6-0.4 -0.20 0.2 0.4 0.6 0.8 1
A researcher is investigating the effectiveness of two weight loss treatments. The number of patients attending Treatment A and Treatment B are 30 and 32 respectively. The patients’ weight losses (in Kg) after a two-month treatment period are recorded and shown in Table 1: What type of research design you think this research should be classified? Explain your answer. Based on the research objective of the study, identify the: Independent and dependent variables of this research. Scale of measurement of each of the independent and dependent variables. For EACH of the treatment, determine/construct the following measures and histograms of weight losses using SPSS or any suitable statistical analysis tool: Mean Median Range Histogram d. Based on the histograms of weight losses produced in (c), briefly describe: The shape of distribution of weight losses for EACH treatment. How does the distribution of Treatment A differ from Treatment B e.…
2. The city council is considering a law that would ban concealed weapons in all public facilities. A sample has been selected from the community and surveyed about support for the proposed ordinance. Is there a statistically significant relationship between age and support for the law against carrying concealed weapons (use p=.05, χ2(critical) = 3.841)? Use the five step model as a guide and write a sentence or two interpreting your results. Age Under 40 40 and older Support For 142 77 219 Against 106 170 276 248 247 495
The condition of an independent variable being correlated to one or more other independent variables is referred to as nonlinearity. statistical significance. multicollinearity. linearity.
Help me please
Early life corresponds to the first bacterial colonization of the digestive tract, creating a microbiome thought to play an important role in human development. What might be the effect of early exposure to antibiotics on children's development? One study followed 11,532 full-term babies all born in the county of Avon, United Kingdom, during 1991 and 1992. Exposures to antibiotics during infancy were recorded, along with measures of body mass at regular intervals over several years. The researchers found that antibiotic exposure during the first six months of life was associated with increased body mass later in childhood.
HDI revisited The United Nations DevelopmentProgramme (UNDP) uses the Human Development Index (HDI) in an attempt to summarize in one number the prog-ress in health, education, and economics of a country. The number of phone subscribers per 100 people is positivelyassociated with economic progress in a country. Can thenumber of phone subscribers be used to predict the HDI?Here is a scatterplot of HDI against phone subscribers:a) Explain why fitting a linear model to these data mightbe misleading.b) If you fit a linear model to the data, what do you think ascatterplot of residuals vs. predicted HDI will look like?
According to a 2006 survey conducted by the Center for Disease Control and Prevention (CDC), birth rates peak slightly between July and October each year. While a slight numerical increase in birth rates is often observed, this difference is assumed to be statistically non-significant. Thus, we would expect to see an equal number of people born during each month of the year in the United States. The "Birth Data.jasp" contains the birth months for 1380 babies (N = 1380) born during the year 2006 in the United States collected by the CDC. Conduct a Chi-Square Goodness of Fit Test at α = 0.05, to see if the number of babies born each month “fits” with the CDC’s assumptions about the population. Identify the correct null hypothesis. A. H0: The number of babies born throughout the year is equal across all 12 months B. H0: The number of babies born during the summer months is greater than the number of babies born during the rest of the year C. HA: The number of babies born in…
Interpret the results presented in the following table. H1: The predictor variables (i.e. Tangibility, Reliability, Responsiveness, Empathy, and Assurance) have an effect on customer satisfaction H2: Tangibility has a positive impact on customer satisfaction. H3: Reliability has a positive impact on customer satisfaction. H4: Responsiveness has a positive impact on customer satisfaction. H5: Empathy has a positive impact on customer satisfaction. H6: Assurance has a negative impact on customer satisfaction.
Please let me know if I calculated relative risk correctly. Thank you for your assistance.

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