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upper and lower limits of error are +0.5 and -0.5 of any number respectively.
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19 pages
Stat Questions
Is there a link between the performance of 1.5-volt batteries and the brand of battery? Null theory: There is no link betw ...
Stat Questions
Is there a link between the performance of 1.5-volt batteries and the brand of battery? Null theory: There is no link between the performance of ...
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Named Hw2yourname
Hence, the least squares line for the data is, Sweetness Index = 6.25 -0.00231Pectin (ppm). Part B: The value of represent ...
Named Hw2yourname
Hence, the least squares line for the data is, Sweetness Index = 6.25 -0.00231Pectin (ppm). Part B: The value of represents the 0.0023 units decrease ...
GCU Monthly Budget Years of Education and Average Income Excel Worksheet
Complete uploaded worksheet using Excel. Please upload in excel format. Complete uploaded Excel worksheet by deadline.
GCU Monthly Budget Years of Education and Average Income Excel Worksheet
Complete uploaded worksheet using Excel. Please upload in excel format. Complete uploaded Excel worksheet by deadline.
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?
6 pages
Afrobarometer Contonuous Variable
The data file that is included in this analysis is Afrobarometer dataset. The categorical and continuous variables from th ...
Afrobarometer Contonuous Variable
The data file that is included in this analysis is Afrobarometer dataset. The categorical and continuous variables from the dataset that will form the ...
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Most Popular Content
19 pages
Stat Questions
Is there a link between the performance of 1.5-volt batteries and the brand of battery? Null theory: There is no link betw ...
Stat Questions
Is there a link between the performance of 1.5-volt batteries and the brand of battery? Null theory: There is no link between the performance of ...
8 pages
Named Hw2yourname
Hence, the least squares line for the data is, Sweetness Index = 6.25 -0.00231Pectin (ppm). Part B: The value of represent ...
Named Hw2yourname
Hence, the least squares line for the data is, Sweetness Index = 6.25 -0.00231Pectin (ppm). Part B: The value of represents the 0.0023 units decrease ...
GCU Monthly Budget Years of Education and Average Income Excel Worksheet
Complete uploaded worksheet using Excel. Please upload in excel format. Complete uploaded Excel worksheet by deadline.
GCU Monthly Budget Years of Education and Average Income Excel Worksheet
Complete uploaded worksheet using Excel. Please upload in excel format. Complete uploaded Excel worksheet by deadline.
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?
6 pages
Afrobarometer Contonuous Variable
The data file that is included in this analysis is Afrobarometer dataset. The categorical and continuous variables from th ...
Afrobarometer Contonuous Variable
The data file that is included in this analysis is Afrobarometer dataset. The categorical and continuous variables from the dataset that will form the ...
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