Question

Sale Price	List Price	Days to Sell	Gulf View
475	495	130	1
350	379	71	1
519	529	85	1
534.5	552.5	95	1
334.9	334.9	119	1
505	550	92	1
165	169.9	197	1
210	210	56	1
945	975	73	1
314	314	126	1
305	315	88	1
800	885	282	1
975	975	100	1
445	469	56	1
305	329	49	1
330	365	48	1
312	332	88	1
495	520	161	1
405	425	149	1
669	675	142	1
400	409	28	1
649	649	29	1
305	319	140	1
410	425	85	1
340	359	107	1
449	469	72	1
875	895	129	1
430	439	160	1
400	435	206	1
227	235	91	1
618	638	100	1
600	629	97	1
309	329	114	1
555	595	45	1
315	339	150	1
200	215	48	1
375	395	135	1
425	449	53	1
465	499	86	1
428.5	439	158	1
217	217	182	0
135.5	148	338	0
179	186.5	122	0
230	239	150	0
267.5	279	169	0
214	215	58	0
259	279	110	0
176.5	179.9	130	0
144.9	149.9	149	0
230	235	114	0
192	199.8	120	0
195	210	61	0
212	226	146	0
146.5	149.9	137	0
160	160	281	0
292.5	322	63	0
179	187.5	48	0
227	247	52	0

Use descriptive statistics to summarize each of the three variables for the 40 Gulf View condos. Describe the distribution of each variable. Repeat for the 18 No Gulf View Condos. (This includes the five-number summary, the mean, standard deviation, and a histogram of each variable). Gulf View condos are denoted by “1” in the Gulf View column, whereas No Gulf View condos are denoted by “0”. Prices are in thousands of dollars.

Answer 1

We will use R commands for the calculations. We may import the data by saving the above table by the name 'dat' and the enter the following command:

library(readr)
> dat <- read_delim("Documents/r/dat", "\t", escape_double = FALSE, trim_ws = TRUE)

Note: Be sure to remove the spaces in each column names, so that the column slices would seem more structured.

The golf view condos can be sliced in the dataframe 'dat1' by the following command:

dat1 <- dat[dat$GulfView==1,]
View(dat1)

Now, entering the command

summary(dat1)

would return the required results of the five number summary as below.

SalePrice (Thousand $)	ListPrice (Thousand $)	DaysToSell (Thousand $)
Min. :165.0	Min. :169.9	Min. : 28.00
1st Qu.:314.8	1st Qu.:334.2	1st Qu.: 71.75
Median :417.5	Median :437.0	Median : 96.00
Mean :454.2	Mean :474.0	Mean :106.00
3rd Qu.:522.9	3rd Qu.:550.6	3rd Qu.:136.25
Max. :975.0	Max. :975.0	Max. :282.00

Standard deviation can be found as commands below:

sd(dat1$SalePrice)

192.5178

sd(dat1$ListPrice)

197.29

sd(dat1$DaysToSell)

52.21602

would give the respective standard deviations.

The histograms would be found by the commands as below:

hist(dat1$SalePrice)
hist(dat1$ListPrice)
hist(dat1$DaysToSell)

and the graphs would be as below.

All the distributions seems positively skewed.

_________________________________________

The non-golf view condos can be sliced in the dataframe 'dat2' by the following command:

dat2 <- dat[dat$GulfView==0,]
View(dat2)

Now, entering the command

summary(dat2)

would return the required results of the five number summary as below.

SalePrice (Thousand $)	ListPrice (Thousand $)	DaysToSell (Thousand $)
Min. :135.5	Min. :148.0	Min. : 48.00
1st Qu.:177.1	1st Qu.:181.6	1st Qu.: 74.75
Median :203.5	Median :212.5	Median :126.00
Mean :203.2	Mean :212.8	Mean :135.00
3rd Qu.:229.2	3rd Qu.:238.0	3rd Qu.:149.75
Max. :292.5	Max. :322.0	Max. :338.00

Standard deviation can be found as commands below:

sd(dat2$SalePrice)

43.89172

sd(dat2$ListPrice)

48.94528

sd(dat2$DaysToSell)

76.29972

would give the respective standard deviations.

The histograms would be found by the commands as below:

hist(dat2$SalePrice)
hist(dat2$ListPrice)
hist(dat2$DaysToSell)

and the graphs would be as below.

The sale price and list price data is quite normally distributed, while the days to sell data is a bit positively skewed.