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HAP602 Harvard University Spouse Depression Case Study 2 Analysis
Use this case study in combination with the Case Study 2 – AA Spouse Depression.xlsx A study in 2005 was conducte ...
HAP602 Harvard University Spouse Depression Case Study 2 Analysis
Use this case study in combination with the Case Study 2 – AA Spouse Depression.xlsx A study in 2005 was conducted to determine whether there was a difference in the depression of women and men who were participating in Alcoholics Anonymous program as well as whether the presence of their spouses at the meetings had a relationship on their depression score. One-hundred-ninety-six men and women participated in the study, and their depression scores after 30 days and 180 days were captured using a depression inventory on which lower scores represented lesser depression. The score range on the instrument is 3 to 24. The data are contained in the file “Case Study 2 - AA Spouse Depression.csv.” You will perform a set of analyses on the data with the file, and then interpret the results to indicate your findings. The column Spouse Present indicates whether the participant was enrolled in an AA program that encouraged spouses to attend (1) or did not allow others except the participant to attend meetings (called closed meetings). In addition, the age and urban or rural residence of the participant is shown. All participants are married whether their spouse attended or not. 1) Prepare a table of the data using the following template. Sex Mean Depression Score, 30 days (sd) Mean Depression Score, 180 days (sd) Mean Age, (sd) Male Attended with spouse Attended without spouse Female Attended with spouse Attended without spouse Based on this information alone, what conclusions can you state? 2) Which group had the most variation in depression scores at 30 days, men or women? Did this change at 180 days?
West Coast University Week 5 Domain of Rational Function Discussion
Complete your Week 5 discussion prompt:
Teach your classmates the process to find the domain of rational function. I ...
West Coast University Week 5 Domain of Rational Function Discussion
Complete your Week 5 discussion prompt:
Teach your classmates the process to find the domain of rational function. Illustrate the concept with two examples, one of which requires factoring. Please include both set notation and interval notation as part of your teaching. Remember that teaching requires detailed explanation, as well as the actual math notation.
Excel:Descriptive Numerical Analysis
Project Description: The present study investigates the distribution of sale prices for homes in a region in upstate New ...
Excel:Descriptive Numerical Analysis
Project Description: The present study investigates the distribution of sale prices for homes in a region in upstate New York. This project will also seek to compare the distributions of sale prices between homes with central air and homes without central air. Suppose you are being transferred to this area and are interested in getting a good description of selling prices for homes in this region. The variables collected in the data are: Price: Recorded in dollars; Lot size: measured in acres; Living Area: measured in square feet; Pct College: percent of students going to college; Central Air: No – 0, Yes – 1; Bedrooms: Number of bedrooms; Fireplace: Number of fireplaces; Bathrooms: Number of bathrooms. For the purpose of this project, you will only be using the variables Price and Central Air. Instructions: For the purpose of grading the project you are required to perform the short 17 steps:
ASALLC Concrete Foundation for a Residential Building Project Worksheet
Refer to Sheets1, 2, 3, and 5 from the Marseille residential building plans in the Large Prints supplement to answer the
...
ASALLC Concrete Foundation for a Residential Building Project Worksheet
Refer to Sheets1, 2, 3, and 5 from the Marseille residential building plans in the Large Prints supplement to answer the
following questions. Complete Activity 10-2 complete the questions and fill in the answers on the form and save as a pdf
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(t ...
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(tidyverse)library(gapminder)# use ?gapminder get the desciption of the dataset `gapminder````
Consider the dataset `gapminder`.
##### (a) Modify the `continent` factor by classifying the Americas' countries into `South America` and `North America` Hint: the following countries are in South America. ```r c("Argentina", "Bolivia", "Brazil", "Chile", "Colombia", "Ecuador", "Paraguay", "Peru", "Trinidad and Tobago", "Uruguay", "Venezuela") ```
In the following questions, use the dataset modified in (a).
Hint: you could use `case_when` function.
##### (b) How many countries are there in the dataset? How about for each continent?
##### (c) For each year, which country had the largest gdp per capital?
##### (d) For each continent, which country experienced the sharpest increment rate in life expectancy from 1997 to 2007?
##### (e) Focus on the data in year 2007, what are the correlation coefficients between life expectancy and gdp per capital for each continent?
##### (f) Visualize part (e) by plotting gdp per capital vs life expectancy.---title: "Question 2"---
Consider the `flights` dataset in the package `nycflights13`.
```{r, message = FALSE}library(nycflights13)library(tidyverse)```
##### (a) Add a column that is the amount of time gained in the air (`gain = dep_delay - arr_delay`)
##### (b) Sort part (a) descedingly by the column you just created. Store the result as `flights_gain`.
##### (c) On average, did flights gain or lose time? (Hint: not average gain, but as percentage of positive gain.)
##### (d) On average, did flights heading to SeaTac ("SEA") gain or loose time?
##### (e) Summerize the mean, min and max of the `air_time` column for flights from `JFK` to `SEA`.
##### (f) In which month was the average departure delay the greatest?
##### (g) In which airport were the average arrival delays the highest?
#####(h) Which city was flown to with the highest average speed?
##### (i) Create a data frame of the average arrival delay for each destination, then use` left_join` to join on the `airports` dataframe, which has the airport info. (Hint: read the documentation of `airports` for the airport codes.)---title: "Question 3"---
##### (a) There is a csv file called `groceries.csv` in this directory. Read the csv file using `read_csv` from `tidyverse` and store the data frame as `groceries`. The datset shows the prices of some common groceries item in 4 different stores.
The table shows the prices of different items in 4 different stores.
##### (b) Is the data frame in wide format or long format?
##### (c) Try to convert it into the other format. Store it as `groceries2`.
##### (d) Use a randomized block design to analysis the store prices. Is there a store marking up the item prices?
Please help me complete this Alg2 study guide
I am working on Alg2 polynomial Functions an I have this study guide
that I need help with so that I can understand how ...
Please help me complete this Alg2 study guide
I am working on Alg2 polynomial Functions an I have this study guide
that I need help with so that I can understand how to do the
computations for my test. Can you please show your work on each
questions, thank you in advance for great help.
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Most Popular Content
HAP602 Harvard University Spouse Depression Case Study 2 Analysis
Use this case study in combination with the Case Study 2 – AA Spouse Depression.xlsx A study in 2005 was conducte ...
HAP602 Harvard University Spouse Depression Case Study 2 Analysis
Use this case study in combination with the Case Study 2 – AA Spouse Depression.xlsx A study in 2005 was conducted to determine whether there was a difference in the depression of women and men who were participating in Alcoholics Anonymous program as well as whether the presence of their spouses at the meetings had a relationship on their depression score. One-hundred-ninety-six men and women participated in the study, and their depression scores after 30 days and 180 days were captured using a depression inventory on which lower scores represented lesser depression. The score range on the instrument is 3 to 24. The data are contained in the file “Case Study 2 - AA Spouse Depression.csv.” You will perform a set of analyses on the data with the file, and then interpret the results to indicate your findings. The column Spouse Present indicates whether the participant was enrolled in an AA program that encouraged spouses to attend (1) or did not allow others except the participant to attend meetings (called closed meetings). In addition, the age and urban or rural residence of the participant is shown. All participants are married whether their spouse attended or not. 1) Prepare a table of the data using the following template. Sex Mean Depression Score, 30 days (sd) Mean Depression Score, 180 days (sd) Mean Age, (sd) Male Attended with spouse Attended without spouse Female Attended with spouse Attended without spouse Based on this information alone, what conclusions can you state? 2) Which group had the most variation in depression scores at 30 days, men or women? Did this change at 180 days?
West Coast University Week 5 Domain of Rational Function Discussion
Complete your Week 5 discussion prompt:
Teach your classmates the process to find the domain of rational function. I ...
West Coast University Week 5 Domain of Rational Function Discussion
Complete your Week 5 discussion prompt:
Teach your classmates the process to find the domain of rational function. Illustrate the concept with two examples, one of which requires factoring. Please include both set notation and interval notation as part of your teaching. Remember that teaching requires detailed explanation, as well as the actual math notation.
Excel:Descriptive Numerical Analysis
Project Description: The present study investigates the distribution of sale prices for homes in a region in upstate New ...
Excel:Descriptive Numerical Analysis
Project Description: The present study investigates the distribution of sale prices for homes in a region in upstate New York. This project will also seek to compare the distributions of sale prices between homes with central air and homes without central air. Suppose you are being transferred to this area and are interested in getting a good description of selling prices for homes in this region. The variables collected in the data are: Price: Recorded in dollars; Lot size: measured in acres; Living Area: measured in square feet; Pct College: percent of students going to college; Central Air: No – 0, Yes – 1; Bedrooms: Number of bedrooms; Fireplace: Number of fireplaces; Bathrooms: Number of bathrooms. For the purpose of this project, you will only be using the variables Price and Central Air. Instructions: For the purpose of grading the project you are required to perform the short 17 steps:
ASALLC Concrete Foundation for a Residential Building Project Worksheet
Refer to Sheets1, 2, 3, and 5 from the Marseille residential building plans in the Large Prints supplement to answer the
...
ASALLC Concrete Foundation for a Residential Building Project Worksheet
Refer to Sheets1, 2, 3, and 5 from the Marseille residential building plans in the Large Prints supplement to answer the
following questions. Complete Activity 10-2 complete the questions and fill in the answers on the form and save as a pdf
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(t ...
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(tidyverse)library(gapminder)# use ?gapminder get the desciption of the dataset `gapminder````
Consider the dataset `gapminder`.
##### (a) Modify the `continent` factor by classifying the Americas' countries into `South America` and `North America` Hint: the following countries are in South America. ```r c("Argentina", "Bolivia", "Brazil", "Chile", "Colombia", "Ecuador", "Paraguay", "Peru", "Trinidad and Tobago", "Uruguay", "Venezuela") ```
In the following questions, use the dataset modified in (a).
Hint: you could use `case_when` function.
##### (b) How many countries are there in the dataset? How about for each continent?
##### (c) For each year, which country had the largest gdp per capital?
##### (d) For each continent, which country experienced the sharpest increment rate in life expectancy from 1997 to 2007?
##### (e) Focus on the data in year 2007, what are the correlation coefficients between life expectancy and gdp per capital for each continent?
##### (f) Visualize part (e) by plotting gdp per capital vs life expectancy.---title: "Question 2"---
Consider the `flights` dataset in the package `nycflights13`.
```{r, message = FALSE}library(nycflights13)library(tidyverse)```
##### (a) Add a column that is the amount of time gained in the air (`gain = dep_delay - arr_delay`)
##### (b) Sort part (a) descedingly by the column you just created. Store the result as `flights_gain`.
##### (c) On average, did flights gain or lose time? (Hint: not average gain, but as percentage of positive gain.)
##### (d) On average, did flights heading to SeaTac ("SEA") gain or loose time?
##### (e) Summerize the mean, min and max of the `air_time` column for flights from `JFK` to `SEA`.
##### (f) In which month was the average departure delay the greatest?
##### (g) In which airport were the average arrival delays the highest?
#####(h) Which city was flown to with the highest average speed?
##### (i) Create a data frame of the average arrival delay for each destination, then use` left_join` to join on the `airports` dataframe, which has the airport info. (Hint: read the documentation of `airports` for the airport codes.)---title: "Question 3"---
##### (a) There is a csv file called `groceries.csv` in this directory. Read the csv file using `read_csv` from `tidyverse` and store the data frame as `groceries`. The datset shows the prices of some common groceries item in 4 different stores.
The table shows the prices of different items in 4 different stores.
##### (b) Is the data frame in wide format or long format?
##### (c) Try to convert it into the other format. Store it as `groceries2`.
##### (d) Use a randomized block design to analysis the store prices. Is there a store marking up the item prices?
Please help me complete this Alg2 study guide
I am working on Alg2 polynomial Functions an I have this study guide
that I need help with so that I can understand how ...
Please help me complete this Alg2 study guide
I am working on Alg2 polynomial Functions an I have this study guide
that I need help with so that I can understand how to do the
computations for my test. Can you please show your work on each
questions, thank you in advance for great help.
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