# data[].attributes.body
Answer the questions:

Which is the age group with the highest rate of going to the cinema? Which one is the lowest?

Within the 2000-2011 period, what is the direction of change (rising/falling) of each line (age group)? (look at the 2000 and 2011 period only)

What is the ranking of each line throughout 11 years? (don’t pay much attention to the miniscule intersection; just look at the overall)

Which direction (year/age group) are you going to group the data?

# data[].attributes.body
Highest rate: 15-24 >< Lowest: 35 and cover

Direction: all increased

Ranking: 1st: 15-24; 2nd: 7-14 (for most of the period); 3rd: 25-35; 4th: 35 and cover

I will group individuals within the age brackets with highest and lowest proportions for the first paragraph, and then it will be the remaining age groups for the second one

# data[].attributes.body
1

Highest rate: 15- 25

Lowest rate: 35 and over

All four witnessed a rising trend throughout the period

1st: 15-24/ 2nd: 7-14/ 3rd: 25-35 / 4th: 35 and over

Grouping: age group

Body 1: 15-24 vs 35 and over (contrast)

Body 2: 7-14 vs 25-35

# data[].attributes.body
-highest: 15-24, lowest: 35 and cover

-all rose

-15-24: remained to rank first

7-14 and 25-35 was equal

35 and cover at the bottom of the survey

-age group

# data[].attributes.body
1. The age group with the highest rate of going to the cinema is those at 15-24. The lowest is those at 35 or over.

2. 15-24: Peaked then decreased

7-14: decreased

25-35: hit rock bottom but the increased

35+: steadily increased

3. Highest: 15-24

Second highest: 7-14

Third highest: 25-35

lowest: 35+

4. Group 1: Highest and lowest

Group 2: the two middle categories

5. Peak: 15-24: between 2010-2011

7-14: 2010

25-35: around 2009

35+: (no peak)

6. age group: 35+

# data[].attributes.body
1. Age group of the highest rate : 15-24

Age group with the lowest rate: starting from the 35s

2. Direction: Rising despite frequent fluctuations

3. 1st : 15-24

2nd: 7-14

3rd: 25-34

4rd: 35 above

4. group 1 : 15-25

group 2 : 7-14 and 25-34

group 3 : 35 and above

# data[].attributes.body
group 15-24 had held the lion's share of cinema visitors, while the age under 35 had gotten the short end of the stick.

2010-2001: group over 35 and group 25-35 witnessed an upsurge while the two lingering groups declined

15-24 and over 35 remained at the vertically highest and lowest point respectively and the line 7-14 and 25-35 intersected

# data[].attributes.body
1.

15-24: Highest rate

35 and over: Lowest rate

2. 15-24: rose

7-14: rose

25-35: Rising

35 and over: Rising

3. 1st: 15-24

2nd/3rd: 7-14/ 25-35

4th: 35 and over

4.

The data should be grouped by age group

# data[].attributes.body
Most stable period: 2000-2005

Most fluctuation: 2006-2011 (sharp

Most peaks: 2010-2011

Age grouping:

15-24

7-14 & 25-35

35+

Peaks:

15-24: 50%+ (2011)

7-14: 37%+ (2010)

25-35: ~33% (2009)

35+: ~15% (2011)

Most stable line: 35+

# data[].attributes.body
-highest rate: 15-24

-lowest rate: 35 and cover

-within the 2000-2001 period, the direction of change of each line: rising

-ranking (from top to bottom): 15-24; 7-14; 25-2-35; 35 and cover

-group 15-24 and 7-14; 25-35 and 35 and cover

# data[].attributes.body
1. Highest: The 15-24 age group

Lowest: The 35 and over age group

2. 15-24 rising ;it starts around 25% and ends above 50%).

7-14 : rising ,it starts around 10% and ends above 30%.

25-35 : rising ;it starts around 10% and ends around 30%.

35 and over: rising it starts around 0% and ends around 10%.

3. first: 15-24

2nd: 7-14

3rd: 25-35

fourth: 35 and over

4. I would group the data by age group. Grouping by year would make it harder to see the overall trends for each age group.

5. ANOTHER :

7-14 and 15-24: show significantly higher percentages of cinema attendance and more pronounced fluctuations, i

25-35 and 35 and over : exhibit lower percentages and smoother trends, suggesting a more stable but less frequent cinema-going habit.

6. 15-24: the highest peak is around 2010/2011, reaching above 55%.

7-14: the highest peak is around 2010, reaching below 40%.

25-35: the highest peak is around 2011, reaching around 30%.

35 and over: the highest peak is around 2010/2011, reaching around 12%.

7. the 35 and over age group line is the most stable.

# data[].attributes.body
1.

Highest: The 15-24 age group has the highest rate.

Lowest: The 35 and over age group has the lowest rate.

2.

All age groups show a rising trend from 2000 to 2011.

3.

- 1st: 15-24

- 2nd: 7-14 and 25-35 (they are very close, and sometimes intersect, making them essentially tied)

- 3rd: 35 and over

4.

age group is the best way to group this data. This allows for a good comparison of the trends between the different demographics.

SECTION 2

1.

We can group them into:

⁃ High Cinema Attendance: 15-24 age group. This group consistently shows the highest percentage and a distinct, more pronounced upward trend with significant fluctuations.

⁃ Mid-Level Cinema Attendance: 7-14 and 25-35 age groups. These two groups exhibit similar patterns, with a gradual increase and some overlapping. Their fluctuation are also similar.

⁃ Low Cinema Attendance: 35 and over age group. This group consistently shows the lowest percentage and a relatively stable, though slowly increasing, trend.

2.

⁃ 15-24: The most noticeable peaks are around 2009 and 2011, reaching above 50%.

⁃ 7-14: The peak is around 2010, reaching approximately 35%.

⁃ 25-35: The peak is also around 2010, reaching approximately 30%.

⁃ 35 and over: The peak is around 2011, reaching approximately 10%.

3.

The 35 and over age group shows the most stable trend. While it does increase, its fluctuations are minimal compared to the other age groups.