Project 2

1)

2)

The white wine data size is more compared to red wine

white wine --> 4899 rows

red wine --> 1600 rows

3)

No null values

Both wines data is checked

note: a NULL means that there is no value, we're looking at a blank/empty cell, and 0 means the value itself is 0. So 0 is not considered as a null value

4)

Checked & found so many duplicates are there & removed in both wine data

5)

After removing all duplicates in each column in both wine data inly a few rows are survived

for red wine

fixed acidity	volatile acidity	citric acid	residual sugar	chlorides	free sulfur dioxide	total sulfur dioxide	density	pH	sulphates	alcohol	quality
7.4	0.7	0	1.9	0.076	11	34	0.9978	3.51	0.56	9.4	5
5.7	1.13	0.09	1.5	0.172	7	19	0.994	3.5	0.48	9.8	4
10.4	0.55	0.23	2.7	0.091	18	48	0.9994	3.22	0.64	10.3	6
15.6	0.685	0.76	3.7	0.1	6	43	1.0032	2.95	0.68	11.2	7

for white wine

fixed acidity	volatile acidity	citric acid	residual sugar	chlorides	free sulfur dioxide	total sulfur dioxide	density	pH	sulphates	alcohol	quality
7	0.27	0.36	20.7	0.045	45	170	1.001	3	0.45	8.8	6
7.9	0.18	0.37	1.2	0.04	16	75	0.992	3.18	0.63	10.8	5
5.2	0.44	0.04	1.4	0.036	43	119	0.9894	3.36	0.33	12.1	8

6)

for white wine mean density is 0.994133

for red wine mean density is 0.9986

7)

combined data set

fixed acidity	volatile acidity	citric acid	residual sugar	chlorides	free sulfur dioxide	total sulfur dioxide	density	pH	sulphates	alcohol	quality
7.4	0.7	0	1.9	0.076	11	34	0.9978	3.51	0.56	9.4	5
5.7	1.13	0.09	1.5	0.172	7	19	0.994	3.5	0.48	9.8	4
10.4	0.55	0.23	2.7	0.091	18	48	0.9994	3.22	0.64	10.3	6
15.6	0.685	0.76	3.7	0.1	6	43	1.0032	2.95	0.68	11.2	7
7	0.27	0.36	20.7	0.045	45	170	1.001	3	0.45	8.8	6
7.9	0.18	0.37	1.2	0.04	16	75	0.992	3.18	0.63	10.8	5
5.2	0.44	0.04	1.4	0.036	43	119	0.9894	3.36	0.33	12.1	8

8)

no null values

note: a NULL means that there is no value, we're looking at a blank/empty cell, and 0 means the value itself is 0. So 0 is not considered as a null value

9)

no outliers

10)

By looking into the details, we can see that good quality wines have higher levels of alcohol on average, have a lower volatile acidity on average, higher levels of sulphates on average, and higher levels of residual sugar on average.

Based on our data YES.

11)

To calculate the correlation between citric acid content and pH, you can use Pearson's correlation coefficient formula. The formula is as follows:

r = (n * Σ(x * y) - Σx * Σy) / sqrt((n * Σx^2 - (Σx)^2) * (n * Σy^2 - (Σy)^2))

where: x = citric acid y = pH n = number of observations (in this case, n = 7) Σ means the sum of all values

Plugging in the values:

r = (7 * (0 + 0.09 * 3.5 + 0.23 * 3.22 + 0.76 * 2.95 + 0.36 * 3 + 0.37 * 3.18 + 0.04 * 3.36) - (0 + 0.09 + 0.23 + 0.76 + 0.36 + 0.37 + 0.04) * (3.51 + 3.5 + 3.22 + 2.95 + 3 + 3.18 + 3.36)) / sqrt((7 * (0^2 + 0.09^2 + 0.23^2 + 0.76^2 + 0.36^2 + 0.37^2 + 0.04^2) - (0 + 0.09 + 0.23 + 0.76 + 0.36 + 0.37 + 0.04)^2) * (7 * (3.51^2 + 3.5^2 + 3.22^2 + 2.95^2 + 3^2 + 3.18^2 + 3.36^2) - (3.51 + 3.5 + 3.22 + 2.95 + 3 + 3.18 + 3.36)^2))

After performing the calculations, the value of r is approximately -0.038, which indicates a weak negative correlation between citric acid content and pH. This means that as the citric acid content increases, the pH value decreases slightly, but the relationship is not strong.

12)

13)

So, in this data set, the number of independent variables would be 11 (fixed acidity, volatile acidity, citric acid, residual sugar, chlorides, free sulfur dioxide, total sulfur dioxide, density, pH, sulphates, alcohol) as these variables can potentially influence or predict the outcome of the dependent variable "quality."

14)

pH	Acidity level
3.51	medium
3.5	medium
3.22	moderately high
2.95	high
3	moderately high
3.18	moderately high
3.36	moderately high

15)

16)

white wine is more quality than red wine

17)

let's calculate thealcohol content less than median

9.4, 9.8, 10.3, 11.2, 8.8, 10.8, 12.1

The median alcohol content is 9.4.

18)

Low alcohol group:

7.4 0.7 0 1.9 0.076 11 34 0.9978 3.51 0.56 9.4 5

5.7 1.13 0.09 1.5 0.172 7 19 0.994 3.5 0.48 9.8 4

7 0.27 0.36 20.7 0.045 45 170 1.001 3 0.45 8.8 6

High alcohol group:

10.4 0.55 0.23 2.7 0.091 18 48 0.9994 3.22 0.64 10.3 6

15.6 0.685 0.76 3.7 0.1 6 43 1.0032 2.95 0.68 11.2 7

7.9 0.18 0.37 1.2 0.04 16 75 0.992 3.18 0.63 10.8 5

5.2 0.44 0.04 1.4 0.036 43 119 0.9894 3.36 0.33 12.1 8

For the low alcohol group quality ratings:

* 5, 4, 6, and 6 are the quality ratings,

* And the mean quality rating is 5.25

For the high alcohol group quality ratings:

* 6, 7, 5, and 8 are the quality ratings,

* And the mean quality rating is 6.5

So, the mean quality rating for the low alcohol group is 5.25 and for the high alcohol group is 6.5.

19)

The relationship between the residual sugar content and the quality rating of wine is not necessarily straightforward, as there are many factors that can affect the overall quality and taste of a wine. Some people may prefer sweeter wines and rate them higher, while others may prefer drier wines and rate them higher. The residual sugar content is just one of many factors that can contribute to the taste and quality of a wine.

20)

To get the number of counts based on ratings and color of wine, we can create a table that groups the data by "color" and "quality" columns. The counts of each group can then be calculated.

For the red wine data:

Quality	Count
4	1
5	2
6	2
7	1

For the white wine data:

Quality	Count
5	1
6	2
8	1

This shows that there are 2 red wines with a quality rating of 5, 2 red wines with a quality rating of 6, 1 red wine with a quality rating of 7, 1 white wine with a quality rating of 5, 2 white wines with a quality rating of 6, and 1 white wine with a quality rating of 8.

21)

No, the density of red wine and white wine is not similar. The density values of red wine range from 0.9978 to 1.0032, while the density values of white wine range from 0.9894 to 1.001. These values show that the density of red wine is generally higher compared to the density of white wine.