Average Hours Of Tv Watched Per Week example essay topic

Introduction. This Data Handling Project is looking at a database based in Excel where there is data from Key Stage 3 and 4 from Mayfield High School. This data consists of several columns containing both Quanta tive and Qualitative Information. Examples of this data are: . Year Group. Name; Surname, Forename 1 and Forename 2.

Age in Months and Years. Month of Birthday. Gender. Hair Colour. Eye Colour.

Left / Right Handed. Favourite Colour. Average number of Hours TV Watched per week. SATS Results etc... In this project I am going to make up several Hypothesis es that I will use the data from the Data Base to help me prove.

However I will not use all of the data, and for each Hypothesis I will Random Sample using the computer 30 entries which fit into certain restrictions applying to that Aim. The Random Sampling method that I am going to use is a computer generated one. The method of doing this is as follows: 1. Filter or sort the necessary data, copy and paste into a new sheet. Add 2 extra columns before this data. In Column 1 leave blank, and in Column 2 type the numbers 1 to X. 2.

In the top of Column 2 type = RAND X, this makes a number between 1 and X. In the top of Column 1 put SUM in. In Column 1 next to that number put the number 1 and press enter, a new number will appear, put a 1 next to that number etc... The amount of 1's you have typed will in the top of Column 1 - continue until 30.3. Copy and paste the selected data into a new sheet so that you can draw graphs and analyse it etc... Do Female Brunettes have higher IQ's that Blonde Females? The hypothesis of this Question that I want to use the data from the Mayfield High School to prove is: The Females from the Mayfield High School in key Stage 4 that have Brown hair are more intelligent, as shown in their IQ Level, that Females in the same age range and from the same School but with Blonde coloured hair?

To get my data and graphs I am going to sort and filter data from the key Stage 4 information. I am going to sort firstly by Hair Colour in ascending order, then by 1 q in ascending order. I will then random sample 30 from each and put these into Categories in a tally table, which I can then turn into 3 graphs: . A Comparison between the Blonde and brunette females in each of the IQ categories... Cumulative Frequency of Brunette Females IQ, . Cumulative Frequency of Blonde Females IQ.

[See following sheets] From sorting and filtering out my necessary data, and drawing up my Graphs I am now going to put this information into Box and Whisker Diagrams [ with graphs for this section ] also finding the average, mean, and mode information. After I have done this I am then going to analyse my findings. Blonde Females IQ. Median = 92 Lower Quartile = 87 Upper Quartile = 95 Brunette Females IQ. Median = 88 Lower Quartile = 85 Upper Quartile = 90 The average IQ for: Blonde Females is: 2679 / 30 = 89.3 Brunette Females is: 2556 / 30 = 85.3 The Mode IQ for: Blonde Females is: 91 (5) Brunette Females is: 90 (8) From looking at all of the graphs and diagrams that I have drawn I have come to the conclusion that there is no real significant change in IQ Levels between Blonde and Brunette Females from Key Stage 4 in the Mayfield High School. This is because all of the data really evens itself out.

The differences between the Blonde and Brunette Females IQ Levels only really showed that there were 2 more Brunettes that had between 96-100 IQ's than the Blondes. This is not really strong evidence to base the statement of fact that Brunettes are more intelligent as they have higher IQ's than the Blondes. The Box and Whisker Diagram for the Blonde Females IQ has a larger Lower Quartile, a smaller Median area, and a larger Upper Quartile than the Brunette Females IQ. The spacing of the sections in these diagrams shows to me that due to the Blonde Females having a smaller Lower Quartile IQ space there are less people in this section than in the Brunette Females section.

As the Upper Quartile is larger for the Blondes than the Brunettes this agrees with the fact that the Blondes appear to be slightly more intelligent and have higher IQ's. However as there is not a real significant difference i. e., by 2 in the Lower Quartile I don't think that this should really be deemed as a final conclusion as if I was to choose different sample data my results may have been more evenly spread for both hair colours. There was one anomaly in this data that I used to answer this Hypothesis. The piece of data that had the Anomaly was a girl in Yr. 11 with Blonde hair and an IQ Level of 11.

I don't think that this is a real piece of data as in the whole IQ Levels for Key Stage 4 there was only 2 students with IQ Levels of under 76. These 2 levels were 11 and 14. Therefore from conducting these graphs I can say that my Hypothesis is not true and that I didn't really find any great significant change in the IQ Levels. Does the Average hours of TV Watched per week affect a persons Weight? The hypothesis of this Question that I want to use the data from the Mayfield High School to prove is: Is the increase in the amount of television watched by pupils in Year 10 reflected by their size, in weight? e.g. does the heaviest person in my sample watch the most TV? What are the most common hours of TV Watched and is there a concentrated result of the same weight shown here?

I am going to sort firstly by Age to filter out all of the Year 10 Students. Then I will delete the irrelevant columns and sample using Random sampling 30 entries. This data will then be sorted into the amount of hours of TV Watched in decreasing order, so that I can then draw up my Graphs. I am going to leave the Gender of the people in my data selection so that I can use this to help me make a more precise and accurate reading from my results in my Conclusion and Analysis of data. The graphs that I am going to draw are going to be: . Frequency of the Hours of TV Watched on Average per week in %, .

Scatter Diagram to show the relationship... Bar Graph to show the Average Weight for each TV Hrs category. [See following sheets] The graph of the Frequency of Hours watched showed me that the most popular amount of hours of watching TV is between 11 and 15 hours, shown on the graph as 24%. From looking at my Data in my Table the mean value is 14 with 4 entries. From these 4 entries of 14 Hrs of TV there are 4 different weights. If I average these weights the average weight comes to [62+42+57+63 = ans/4] = 56 Kg.

To answer the question of "does the heaviest person in my sample watch the most TV?" I am going to average all of the weights for each different hrs of TV Watched and plot this in a bar graph. [Bar Graph on the next page] The results from this table and graph show me that there is no real relation from student central. co. uk ship between the heaviest person and the fact that they watch the most television, as predicted in my Hypothesis. This is shown from the fact that the heaviest person watches only 15 Hrs of TV and the person who watches the most TV weighs only 68 Kg. Unfortunately from looking at my Graphs I think that there is once again no real correlation between the size of someone and the amount of TV that they watch. However if I look at my Scatter Diagram I can see that, ignoring the anomaly (in a yellow circle), there does seem to be some weak negative correlation. However from looking at the Scatter Diagram even more I can see that this weak positive correlation isn't coming from the fact that the heaviest person watches the most TV but more like the less TV that is watched means that they are of an average weight.

This seems to apply until we get to above 20 Hrs of watching TV a week where the results seem to spread up and down. I think that this signifies that when the hours of TV is increased some peoples weight does either increase or decrease from the original concentrated area (average weight). There was one anomaly in my data and this was a male who watched 65 hours of TV a week and Weighed 68 Kg. The reason that I think this is an anomaly is because it is literally impossible to watch this amount of TV a week when the person has to attend school and complete homework of an evening. Also the next person down in my sample only watches 48 hours of TV, so there is a difference range of [68 - 48] 20 Hours. The Conclusion to my analysis of data is that my Hypothesis is not true.

However from conducting this research and graphs I think that it is evident that the less TV is watched the more that person is of an average weight. Do Girls in general have a higher IQ than Boys in the same years? The hypothesis of this Question that I want to use the data from the Mayfield High School to prove is:.