Assignment 3

.Continue to use the data set of assignment2 Download assignment2from Canvas and save on your hard drive.Get into Excel and load the data set of assignment 2

Use online chi-square calculator to perform a chi-square test to see whether there is a relationship between using the new software and job satisfaction.( https://www.socscistatistics.com/tests/chisquare2/default2.aspx)
Use Analysis Toolpak to conduct a bivariate regression, using productivity as dependent variable and software as independent variable. Interpret the intercept (constant term) and the coefficient of software.
Use Analysis Toolpak to conduct a multiple regression, using productivity as dependent variable. The independent variables include software, education, experience, job satisfaction and age. Interpret the intercept and coefficients. What does the F-statistic tell you? What does the R-square tell you?Based on the t-statistics, what can we say about the relationship between the independent variables and productivity in the population?
You will continue to evaluate the analysis memo in Assignment 2. Here is the context again

You ask your analyst to examine data on service delivery across substance abuse treatment providers in three cities: Chicago, IL; Washington, D.C.; and, Los Angeles, CA. Each provider in this data set treats individuals with alcohol and/or drug use problems. In addition to basic information about the characteristics of clients, the data file contains some basic information on the dimensions of services delivery or of services offered. The dataset also includes a measure of program success—the percent of clients free of substance use for 6 months (both alcohol and drugs). This has been determined from several random drug tests given the clients during the time. (Clients had to agree to the drug tests to participate in the program. Ignore the legal issues surrounding this, and assume no attrition of clients.) You are now ready to look at the impact that the different dimensions of these programs have on the clients remaining substance free. All of the persons in the dataset have experienced some type of treatment, so there is no comparison group, which received no treatment. However, the clients have attended different providers, which provide a different array of services. Unfortunately, the data is only available at the provider level, not individual client. You have collected some control variables to reflect the differences in the client population served by each center.

Dimensions of Service Delivery

cityid

City identifier

hotline

Does facility operate or staff a hotline that provides substance abuse counseling and/or
referrals?

prevntn

Does the facility offer preventative services?

facility

Type of facility. Inpatient clinics involve overnight or long-term stays for more severe problems, outpatient clinics treat and release patients with less severe problems.

waitlist

Does the facility maintain a waitlist that notifies clients when a service slot or opening exists?

waitnum

Number of people on the waitlist.

socserv

Does the facility help clients locate additional governmental social services (i.e., welfare, food stamps, Medicaid)?

healthed

Does the facility offer health education services (i.e., nutrition, infectious disease, STDs)?

parent

Does the facility offer parenting or family skills development?

Three days later, the analyst gives you the analysis.

Please discuss what you get from the analysis in the attachment ; what do you want to know further; and your evaluation of the analysis. Focus on the following points.

How do you evaluate the analysis? Is it sufficient to inform you of the service delivery among these three cities?
What else do you want to know?
What other analysis would you like to ask your analysis to conduct?
How do you evaluate the analysis?
The Analysis Memo

In the following memo, we will examine data on service delivery for substance abuse treatment providers in three cities: Chicago, Il, Washington, DC and Los Angeles, CA. Each provider in the data set treats individuals with alcohol and/or drug use problems. Aside from this basic characteristic, additional basic information on client characteristics included patients’ age, ethnicity, gender, whether they were single mothers or not and the percent of clients who remained alcohol and/or drug free for six months of treatment. At the same time, we examined several characteristics for each of the three providers, including the provider’s location, whether the providers offer a hotline and preventive services, whether the providers are an inpatient or outpatient, whether or the providers have a wait list and, if so, how many people are on the list, and whether or not the providers assist their patients with seeking social services, health education services and parenting or family skills development.

The data is displayed at the providers’ level, but every single patient included in the data has received some type of treatment. Each provider provides a different array of services and the following memo will look at the different dimensions of these programs and their impact on keeping the clients substance free.

We will look at how service delivery varies across the three cities. For starters, we can see that for most of the patients, hotline services are not provided across all three cities, with those in Los Angeles, CA receiving the least amount of help here. Los Angeles also showed a higher rate of prevention services, with both Washington, D.C. and Chicago, IL providers split down the middle in this service area. Both Los Angeles and Chicago showed a significant preference towards in-patient services, whereas Washington was, again, split down the middle with their in-patient verses out-patient services. Washington did, however, show a higher rate in favor of not having too many people on their waiting list, while Los Angeles did and Chicago was pretty much split even either way. Neither city had many people on their waiting lists. More patients in Los Angeles and Chicago did not receive assistance with social services than in Washington. Moreover, patients in all three cities received less health education services than the number that did. Likewise, more patients in all three cities did not receive parenting/family skills development training than the number that did.

In taking a closer look at the patients across all three cities, we come to see that patients in Los Angeles are more likely to have drug related problems, with Chicago patients the least likely. However, in terms of alcohol abuse, the number of Washington and Chicago patients was pretty much neck and neck, with the number of patients from Los Angeles trailing behind. Most cities’ patients were between twenty-five to thirty-four years of age and while most of Washington’s patients were black, most of Los Angeles’ and Chicago’s patients were white. Interestingly, Chicago had the highest number of both male and female patients. Patients in Los Angeles were more likely to be single moms, followed by Chicago and then Washington. Most importantly though, when examining the number of patients who were substance free for six months, Los Angeles showed the least number of patients, while Chicago and Washington came in (almost neck to neck) almost double the number of patients as Los Angeles. Thus, one could conclude that both the programs in Chicago and Washington showed more favorable results with patients who demonstrated success at refraining from substance abuse with six month of treatment.

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