Lesson 3 Data Commentary You may or may not need to work on Language Focus in this handout (You most probably do not need to print those pages ifyou would prefer reading the paper copy of this handout).All exercises are obligatory. Your chosen research articles from top journals in your discipline (in virtual pdf version)are supposed to be brought to the classroom and copied to corresponding folders respectively on the classroom computer in L3.You may need to read a part of your chosen journal articles in L3. Lesson 3 Reading and Writing the Results I:Data Commentary The Results section presents the outcome of the investigation.The goal in writing the section is more than to simply present the results of your investigation;it is to make them understandable for readers. Data Commentary is the indispensable unit of the Results,and of everyday delivery of ideas. If you have a great deal of data to present,do so in three stages. 1)Give a general overview in one or two sentences.For example,"The results obtained indicate that the film temperature increases as the rolling velocity or slide-roll ratio increases." 2)Present representative data,not the whole mass of data obtained.This is particularly important if an experiment or set of experiments were repeated several times. 3)If it is necessary to provide more than the representative data,do so in an Appendix, not in the text of your paper.This would also be done for interesting data observed but which otherwise did not affect the outcome of your investigation. If you have a great deal of data to present,do not hesitate to use figures and tables We use the term display/figure to include charts,diagrams,drawings,and photographs.Rely upon your text to describe your findings,pointing out the most significant and comprehensive findings presented in your displays.The human mind is capable of grasping a great deal of complex information when presented in a graphic than when presented in text."A picture is worth a thousand words."While in your text you can point out data that is displayed in a table,do not repeat the data in both places.This redundancy only adds unnecessary bulk to your paper. Findings can be described and commented upon in four different ways:statement of fact,behavior over a range,comparison and contrast,and cause and effect.The following are examples of the former two. Statement of fact: It was verified that the average error in fuel spray droplet size is less than 10%. Behavior over a range: The interface between the saturated and unsaturated regions existed,but did not continue to exist when the water content was increased.The temperature at which the maximum concentration of H-related donor occurs increases slightly with thermal neutron dose. Describe any negative results of your investigation.That is,state what you 1/12
Lesson 3 Data Commentary 1 / 12 You may or may not need to work on Language Focus in this handout (You most probably do not need to print those pages if you would prefer reading the paper copy of this handout). All exercises are obligatory. Your chosen research articles from top journals in your discipline (in virtual pdf version) are supposed to be brought to the classroom and copied to corresponding folders respectively on the classroom computer in L3. You may need to read a part of your chosen journal articles in L3. Lesson 3 Reading and Writing the Results I: Data Commentary The Results section presents the outcome of the investigation. The goal in writing the section is more than to simply present the results of your investigation; it is to make them understandable for readers. Data Commentary is the indispensable unit of the Results, and of everyday delivery of ideas. If you have a great deal of data to present, do so in three stages. 1) Give a general overview in one or two sentences. For example, “The results obtained indicate that the film temperature increases as the rolling velocity or slide-roll ratio increases.” 2) Present representative data, not the whole mass of data obtained. This is particularly important if an experiment or set of experiments were repeated several times. 3) If it is necessary to provide more than the representative data, do so in an Appendix, not in the text of your paper. This would also be done for interesting data observed but which otherwise did not affect the outcome of your investigation. If you have a great deal of data to present, do not hesitate to use figures and tables. We use the term display/figure to include charts, diagrams, drawings, and photographs. Rely upon your text to describe your findings, pointing out the most significant and comprehensive findings presented in your displays. The human mind is capable of grasping a great deal of complex information when presented in a graphic than when presented in text. “A picture is worth a thousand words.” While in your text you can point out data that is displayed in a table, do not repeat the data in both places. This redundancy only adds unnecessary bulk to your paper. Findings can be described and commented upon in four different ways: statement of fact, behavior over a range, comparison and contrast, and cause and effect. The following are examples of the former two. Statement of fact: It was verified that the average error in fuel spray droplet size is less than 10%. Behavior over a range: The interface between the saturated and unsaturated regions existed, but did not continue to exist when the water content was increased. The temperature at which the maximum concentration of H-related donor occurs increases slightly with thermal neutron dose. Describe any negative results of your investigation. That is, state what you
Lesson 3 Data Commentary expected to find during your investigation but did not.What an investigation did not uncover often is of as great importance as what was uncovered. Briefly,data commentary goes as follows: Present the subject of the data Make a general comment on the main trend Describe the significant features ● If appropriate,compare/contrast various aspects of the data Conclude by generalizing what you see as the significance in the data performance.This should be based on evidence. I.Recommended reading: pp.91-153in Glasman-Deal,H.(2010).Science Research Writing:For Non-Native Speakers of English.Unit 3 Writing about Results.Imperial College Press. II.Writing the data commentary Generally key elements in data commentary are: location elements and /or summary statements; general/specific highlighting statements; significance,problems,exceptions,etc.in the data. The focus is on highlighting the significant data. Sample Data Commentary: [Location;Summary statement]Table 5 shows the most common modes of infection for U.S businesses. [Specific highlight 1]As can be seen,in the majority of cases,the source of viruses infection can be defected,with disks being brought to the workplace from home being by far the most significant(43%).[Specific highlight 2]However,it is alarming to note that the source of nearly 30%of viruses cannot be determined. [Problem;Significance]While it may be possible to eliminate home-to-workplace infection by requiring computer users to run antiviral software on diskettes brought from home,businesses are still vulnerable to major data loss, especially from unidentifiable sources of infection. 1.Voice Sentence structure Many data commentary sections begin with a sentence containing two elements: location elements and/or summary statements.In English the active voice is as appropriate as the passive voice in this sentence. ·Active voice:: Location Summary ·Table5 shows the most common modes of computer infection for U.S.businesses. Table 2 provides details of the fertilizer used. ·Figure4.2 gives the results of the second experiment. Passive voice: 2/12
Lesson 3 Data Commentary 2 / 12 expected to find during your investigation but did not. What an investigation did not uncover often is of as great importance as what was uncovered. Briefly, data commentary goes as follows: Present the subject of the data Make a general comment on the main trend Describe the significant features If appropriate, compare/contrast various aspects of the data Conclude by generalizing what you see as the significance in the data performance. This should be based on evidence. I. Recommended reading: pp. 91-153 in Glasman-Deal, H. (2010). Science Research Writing: For Non-Native Speakers of English. Unit 3 Writing about Results. Imperial College Press. II. Writing the data commentary Generally key elements in data commentary are: location elements and /or summary statements; general/specific highlighting statements; significance, problems, exceptions, etc. in the data. The focus is on highlighting the significant data. Sample Data Commentary: [Location; Summary statement] Table 5 shows the most common modes of infection for U.S businesses. [Specific highlight 1] As can be seen, in the majority of cases, the source of viruses infection can be defected, with disks being brought to the workplace from home being by far the most significant (43%). [Specific highlight 2]However, it is alarming to note that the source of nearly 30% of viruses cannot be determined. [Problem; Significance] While it may be possible to eliminate home-to-workplace infection by requiring computer users to run antiviral software on diskettes brought from home, businesses are still vulnerable to major data loss, especially from unidentifiable sources of infection. 1. Voice & Sentence structure Many data commentary sections begin with a sentence containing two elements: location elements and/or summary statements. In English the active voice is as appropriate as the passive voice in this sentence. Active voice: Location Summary Table 5 shows the most common modes of computer infection for U.S. businesses. Table 2 provides details of the fertilizer used. Figure 4.2 gives the results of the second experiment. Passive voice:
Lesson 3 Data Commentary Summary location ◆ The most common modes of infection are shown in table 5. Details of the fertilizer used are provided in table 2 The results of the second experiment are given in figure 4.2. 2.Highlighting statements Highlighting statements are generalizations that you draw from the details of the data displayed.It takes good judgment to make a highlighting statement.It is an opportunity to show your intelligence to your readers.In particular,it is an opportunity to demonstrate: that you can spot trends or regularities in the data; that you can separate more important findings from less important ones; that you can make claims of appropriate strength. DO NOT simply repeat all the details in words; attempt to cover all information; claim more than is reasonable or defensible Highlighting statements are usually ordered from general to specific.In other words,major claims are followed by minor claims. 3.Tenses Describe the results of an experiment in the past tense,as the experiment occurred in the past.For findings you conclude from the experiment or your investigation,use the present tense;these are facts which are true now and continue to exist.Mention of figures and tables should be in the present tense;they exist now. 4.High-frequency expressions in data commentary Nouns rise,increase,fall,drop,decrease,fluctuation,downward trend, peak,steep fall,spike,minimum/maximum,local minimum/maximum,linear increase,kink,spike,low point Verb rise,increase,fall,drop,decrease,stabilize,fluctuate,level off Accompanying steady/steadily;sharp;dramatic/dramatically;rapid/rapidly; adjective/adverb slow/slowly; significant/significantly; unexpectedly; noticeable/noticeably Which high-frequency expressions are used in writing the data commentary in your discipline? 5.Terms to refer to Location Inviting your readers to look at an illustration,you have to be able to specify what type of display you refer to,especially when it is not a table. Display Examples Diagrams flow charts,electrical schematics,models(e.g.networks) Illustrations photographs,drawings(e.g.an apparatus/experimental set-up) Maps political,physical,geological maps depicting phenomena 3/12
Lesson 3 Data Commentary 3 / 12 Summary location The most common modes of infection are shown in table 5. Details of the fertilizer used are provided in table 2. The results of the second experiment are given in figure 4.2. 2. Highlighting statements Highlighting statements are generalizations that you draw from the details of the data displayed. It takes good judgment to make a highlighting statement. It is an opportunity to show your intelligence to your readers. In particular, it is an opportunity to demonstrate: that you can spot trends or regularities in the data; that you can separate more important findings from less important ones; that you can make claims of appropriate strength. DO NOT simply repeat all the details in words; attempt to cover all information; claim more than is reasonable or defensible. Highlighting statements are usually ordered from general to specific. In other words, major claims are followed by minor claims. 3. Tenses Describe the results of an experiment in the past tense, as the experiment occurred in the past. For findings you conclude from the experiment or your investigation, use the present tense; these are facts which are true now and continue to exist. Mention of figures and tables should be in the present tense; they exist now. 4. High-frequency expressions in data commentary Nouns rise, increase, fall, drop, decrease, fluctuation, downward trend, peak, steep fall, spike, minimum/maximum, local minimum/maximum, linear increase, kink, spike, low point Verb rise, increase, fall, drop, decrease, stabilize, fluctuate, level off Accompanying adjective/adverb steady/steadily; sharp; dramatic/dramatically; rapid/rapidly; slow/slowly; significant/significantly; unexpectedly; noticeable/noticeably Which high-frequency expressions are used in writing the data commentary in your discipline? 5. Terms to refer to Location Inviting your readers to look at an illustration, you have to be able to specify what type of display you refer to, especially when it is not a table. Display Examples Diagrams flow charts, electrical schematics, models (e.g. networks) Illustrations photographs, drawings (e.g. an apparatus/experimental set-up) Maps political, physical, geological maps depicting phenomena
Lesson 3 Data Commentary (a middle ground between diagrams and pictures) Montages hybrids(combined display,e.g.of a graph and a photograph) Graphs line graphs,bar graphs,scatter plots,pie charts Ex.3-1 Work in groups to revise the draft data commentary on the figure below.Be prepared to share the re-written version with the class. Survival Time in Water of Different Temperatures When Wearing Different Types of Clothing 10 Bohr 一-Wat-Sut (5-mm neoprene) +-Ordinary Clothing 9 11 13 15 Based on Noakes,2000. Draft: The figure shows how long people can survive in water when they wear different kinds of clothing that have different levels of insulation.Clothing has an influence on how long a person can survive.The effect of clothing is greater at warmer temperatures.A person wearing no clothing in cold water survive only less than one hour. Ex.3-2 Discuss with your team to present the significance of the three charts below by applying what has been covered up till now on data commentary.Be prepared to contribute your idea on any of the three to the class. Chart 1 Sales of products,2005-2012 unitssold 12000 10000 8000 6000 4000 2000 20052006200720082009201020112012 Chart 2 4/12
Lesson 3 Data Commentary 4 / 12 (a middle ground between diagrams and pictures) Montages hybrids (combined display, e.g. of a graph and a photograph) Graphs line graphs, bar graphs, scatter plots, pie charts Ex. 3-1 Work in groups to revise the draft data commentary on the figure below. Be prepared to share the re-written version with the class. Survival Time in Water of Different Temperatures When Wearing Different Types of Clothing Draft: The figure shows how long people can survive in water when they wear different kinds of clothing that have different levels of insulation. Clothing has an influence on how long a person can survive. The effect of clothing is greater at warmer temperatures. A person wearing no clothing in cold water survive only less than one hour. Ex. 3-2 Discuss with your team to present the significance of the three charts below by applying what has been covered up till now on data commentary. Be prepared to contribute your idea on any of the three to the class. Chart 1 Chart 2
Lesson 3 Data Commentary Travel Styles of Visitors,2012. Independent Traveler. 14% Package Traveler. 18% 68% Tour Group. Chart 3 Main Accommodation Types Used by Visitors,2012. ■Holiday■Tota Private Homes Motels Hotels 40 60 III.Language Focus---Display Description: 1.Making a comparison: x times as much/many n. as n. x times the n. of n. as n more/less than x times the n.of n.(as n. more/less than x times-er than the n.of n. more/less than x times-er than that of n. more/less than x%-er than that of n. Ex 3-3:Identify how comparison is made in the following sentences. 1)Women typically require twice the dosage of morphine as men to achieve the same degree of pain relief. 2)Each year,the average probability of dying from motor vehicle accidents in France was more than 12 times higher than the risk of drowning. 3)The median wage of a college graduate is now more than 70 percent higher than that of a high school graduate. 4)China produces four times as many engineers as the United States does. 5)Greece consumes more than double the amount of cheese as Denmark. 2.Displays:Guarantee that you know which display best presents what type of information,especially diagrams graphs. When the information has been collected,it is usually analyzed using various statistical techniques.It is then presented in tables,graphs,or charts. 2.1 Tables 5/12
Lesson 3 Data Commentary 5 / 12 Chart 3 III. Language Focus --- Display Description: 1. Making a comparison: x times as much/many n. as n. x times the n. of n. as n. more/less than x times the n. of n. (as n. ) more/less than x times –er than the n. of n. more/less than x times –er than that of n. more/less than x% –er than that of n. Ex 3-3: Identify how comparison is made in the following sentences. 1) Women typically require twice the dosage of morphine as men to achieve the same degree of pain relief. 2) Each year, the average probability of dying from motor vehicle accidents in France was more than 12 times higher than the risk of drowning. 3) The median wage of a college graduate is now more than 70 percent higher than that of a high school graduate. 4) China produces four times as many engineers as the United States does. 5) Greece consumes more than double the amount of cheese as Denmark. 2. Displays: Guarantee that you know which display best presents what type of information, especially diagrams & graphs. When the information has been collected, it is usually analyzed using various statistical techniques. It is then presented in tables, graphs, or charts. 2.1 Tables
Lesson 3 Data Commentary Country of Origin of Students on Foundation Course Female Male China 30 40 Japan 2 8 India 1 7 Pakistan 1 4 Thailand 3 1 Malaysia 2 Tables: are efficient,enabling the researcher to present a large amount of data in a small space show exact numerical values present quantitative data-they need interpreting emphasize the discrete rather than the continuous. They do NOT easily show: the number of students on the course the percentage of female students the percentage of female students from China relationships or trends. 2.2 Pie charts Pie charts can be used to show the sizes of various parts of the results in relation to each other and in relation to the whole sample. Pet Ownership 5%4% 6% ■Dog5 ■Cats ■Fish 30% 55% ■Rabbits ■Rodents In the pie chart above: the circle represents the percentage of people who own various pets; each segment represents the number of people who own different pets; it clearly shows that the largest number of pet ownership is "dog ownership", which means that most people represented in this chart own a dog as opposed to a cat,fish,or other animal; 6/12
Lesson 3 Data Commentary 6 / 12 Country of Origin of Students on Foundation Course Female Male China 30 40 Japan 2 8 India 1 7 Pakistan 1 4 Thailand 3 1 Malaysia 2 1 Tables: are efficient, enabling the researcher to present a large amount of data in a small space show exact numerical values present quantitative data - they need interpreting emphasize the discrete rather than the continuous. They do NOT easily show: the number of students on the course the percentage of female students the percentage of female students from China relationships or trends. 2.2 Pie charts Pie charts can be used to show the sizes of various parts of the results in relation to each other and in relation to the whole sample. In the pie chart above: the circle represents the percentage of people who own various pets; each segment represents the number of people who own different pets; it clearly shows that the largest number of pet ownership is “dog ownership”, which means that most people represented in this chart own a dog as opposed to a cat, fish, or other animal;
Lesson 3 Data Commentary it also shows that rodents make up the smallest number of pets; it tells us that for pet owners,when choosing pets,rodents are at the bottom of their list;that's not to say that rodents make the worst pets,but the data shows that pet owners prefer dogs first and foremost,followed by cats,then fish,then rabbits,then rodents. 2.3 Histograms Histograms (or bar or column graphs)can also be used to describe results. However,they more clearly show the relationship of different parts of the sample to each other.They do not clearly show the parts in relation to the whole. Country of Origin of Students on Foundation Course 必 Female 40 Male 35 30 25 20 15 10 5 0 China Japan India Pakistan Thailand Malaysia The histogram above clearly shows: the proportion of male to female students which country has the most students which country has the fewest women the number of students from India. It does NOT easily show: the number of students on the course the percentage of female students ● the percentage of female students from China. 2.4 Line graphs Line graphs are often used to show the results of studies,especially when they involve some kind of change over time.This usually involves two groups of measurements which are known as variables. 7/12
Lesson 3 Data Commentary 7 / 12 it also shows that rodents make up the smallest number of pets; it tells us that for pet owners, when choosing pets, rodents are at the bottom of their list; that’s not to say that rodents make the worst pets, but the data shows that pet owners prefer dogs first and foremost, followed by cats, then fish, then rabbits, then rodents. 2.3 Histograms Histograms (or bar or column graphs) can also be used to describe results. However, they more clearly show the relationship of different parts of the sample to each other. They do not clearly show the parts in relation to the whole. The histogram above clearly shows: the proportion of male to female students which country has the most students which country has the fewest women the number of students from India. It does NOT easily show: the number of students on the course the percentage of female students the percentage of female students from China. 2.4 Line graphs Line graphs are often used to show the results of studies, especially when they involve some kind of change over time. This usually involves two groups of measurements which are known as variables
Lesson 3 Data Commentary English Test Sores of Students on Course 6 0 9121518212427 Length of study (months) The graph above shows the differences in the English test score of the students on the course. The two variables are the length of time the students have studied English and the students'test scores. The length of study causes the change.(This is called the independent variable and the other-the test score-the dependent variable.) The length of study is on the horizontal(x)axis. The test score is on the vertical (y)axis. Line graphs show well: trends tendencies (-you can see that the test score generally increases as the length of study increases) that a typical student who has studied for 12 months has a score of 4 on the test that a typical student who has scored 6 on the test will have studied for 18 months. In the graph below: English Test Scores of Students on Course 12 10 8 6 4 2 0 3456 7 Test score The independent variable is now the test score. The dependent variable is the number of students who obtained a particular score. The highest score is 7 the lowest score is 1. 8/12
Lesson 3 Data Commentary 8 / 12 The graph above shows the differences in the English test score of the students on the course. The two variables are the length of time the students have studied English and the students' test scores. The length of study causes the change. (This is called the independent variable and the other - the test score - the dependent variable.) The length of study is on the horizontal (x) axis. The test score is on the vertical (y) axis. Line graphs show well: trends & tendencies (- you can see that the test score generally increases as the length of study increases) that a typical student who has studied for 12 months has a score of 4 on the test that a typical student who has scored 6 on the test will have studied for 18 months. In the graph below: The independent variable is now the test score. The dependent variable is the number of students who obtained a particular score. The highest score is 7 the lowest score is 1
Lesson 3 Data Commentary The most common score is 5. .8 students achieved a score of 4. 3.The average The average is a measure of central tendency.It is related to the middle point in a range of scores and is found in many different kinds of research.It can be calculated in three main ways.Most commonly,it refers to what mathematicians call the mean.This is calculated by adding all the scores together and then dividing by the number of scores.For example,if five students obtain the following test scores:2.5,3, 3,4 5,then the average test score (the mean)is 17.5 (the total)divided by 5 (number of students)=3.5.You can see in this case,though,that none of the students actually obtained a score of 3.5. Sometimes it is not useful to calculate the average in this way.For example,we may want to see which score on the test was most frequently obtained.This kind of average,referring to the most frequent score,is called the mode,and is also a very useful average.In this case the mode is 5.10 students obtained a score of 3. The third useful average is the median-this is the middle score obtained by the students on the test.In this case the median is 3. 4.Dispersion Dispersion is the spread of scores.Whereas the various averages will give us information about central tendency,it does not give very much information about the group as a whole.We need to know more about a set of scores than the mean can tell us One useful piece of information is the range from the bottom to the top score.In the example above when five students obtain the following test scores:2.5,3,3,4 5, the range is the difference between the bottom score and the top score,inclusive of both scores,i.e.2.5. It is common to plot the range of scores on a graph.This can show easily the range of scores(from the lowest to the highest)as well as the number of students who obtained each score.For example,if the scores of 69 students are plotted on a graph, it would look something like the diagram below. English Test Scores of Students on Course 10 6 2 4 5 Test score If the sample of sixty-nine students was representative of the students at the 9/12
Lesson 3 Data Commentary 9 / 12 The most common score is 5. 8 students achieved a score of 4. 3. The average The average is a measure of central tendency. It is related to the middle point in a range of scores and is found in many different kinds of research. It can be calculated in three main ways. Most commonly, it refers to what mathematicians call the mean. This is calculated by adding all the scores together and then dividing by the number of scores. For example, if five students obtain the following test scores: 2.5, 3, 3, 4 & 5, then the average test score (the mean) is 17.5 (the total) divided by 5 (number of students) = 3.5. You can see in this case, though, that none of the students actually obtained a score of 3.5. Sometimes it is not useful to calculate the average in this way. For example, we may want to see which score on the test was most frequently obtained. This kind of average, referring to the most frequent score, is called the mode, and is also a very useful average. In this case the mode is 5. 10 students obtained a score of 3. The third useful average is the median - this is the middle score obtained by the students on the test. In this case the median is 3. 4. Dispersion Dispersion is the spread of scores. Whereas the various averages will give us information about central tendency, it does not give very much information about the group as a whole. We need to know more about a set of scores than the mean can tell us. One useful piece of information is the range from the bottom to the top score. In the example above when five students obtain the following test scores: 2.5, 3, 3, 4 & 5, the range is the difference between the bottom score and the top score, inclusive of both scores, i.e. 2.5. It is common to plot the range of scores on a graph. This can show easily the range of scores (from the lowest to the highest) as well as the number of students who obtained each score. For example, if the scores of 69 students are plotted on a graph, it would look something like the diagram below. If the sample of sixty-nine students was representative of the students at the
Lesson 3 Data Commentary university as a whole,then the most common score of university students would be 50%,and the majority of students would have scores around 50%,with a few students at either extreme.See the diagram below.Idealized curves such as the one shown below are called normal distribution curves.The number of people on one side of the centre is the same as on the other side,with about 50%of the students near the centre. English Test Scores of Students on Course 507 20 10 34567 8 9 10 Test score One common measure of how much the scores are spread is the standard deviation(SD).This shows how much the range of scores deviate from the mean.In a normal distribution 68%of the population will get scores within one standard deviation of the mean and so 32%of the population will have scores more than one standard deviation away from the mean.95%of the population will have scores within two standard deviations of the mean. Assignments: 1.Individual work: On the basis of your presentation performance today (Lesson 3)and feedback from your audience,search online for presentation skills and tips,and set your specific goals in improving your presentation performance over this semester.Be ready to justify your goals and share them with the class. 2.Read pp.91-153 in Glasman-Deal,H.(2010).Science Research Writing:For Non-Native Speakers of English.Unit 3 Writing about Results.Imperial College Press. 3. Individual work: Examine the data from your instructor,list factual findings from closer observation and label the data commentary elements.Follow the template.It would be the plan of your first individual written assignment to submit. Requirements: (When necessary,)You are supposed to strategically and effectively incorporate sources (citation paraphrase)with proper documentation (in-text documentation references).Below a reference,cite accurately the extract you particularly refer to. The assignment would be DUE on early W3 classroom morning. Hand in your plan in font size 12 Times New Roman.The labels are to be in bold letters and in brackets ]Entitle your virtual copy "M**+ 10/12
Lesson 3 Data Commentary 10 / 12 university as a whole, then the most common score of university students would be 50%, and the majority of students would have scores around 50%, with a few students at either extreme. See the diagram below. Idealized curves such as the one shown below are called normal distribution curves. The number of people on one side of the centre is the same as on the other side, with about 50% of the students near the centre. One common measure of how much the scores are spread is the standard deviation (SD). This shows how much the range of scores deviate from the mean. In a normal distribution 68% of the population will get scores within one standard deviation of the mean and so 32% of the population will have scores more than one standard deviation away from the mean. 95% of the population will have scores within two standard deviations of the mean. Assignments: 1. Individual work: On the basis of your presentation performance today (Lesson 3) and feedback from your audience, search online for presentation skills and tips, and set your specific goals in improving your presentation performance over this semester. Be ready to justify your goals and share them with the class. 2. Read pp. 91-153 in Glasman-Deal, H. (2010). Science Research Writing: For Non-Native Speakers of English. Unit 3 Writing about Results. Imperial College Press. 3. Individual work: Examine the data from your instructor, list factual findings from closer observation and label the data commentary elements. Follow the template. It would be the plan of your first individual written assignment to submit. Requirements: (When necessary,) You are supposed to strategically and effectively incorporate sources (citation / paraphrase) with proper documentation (in-text documentation & references). Below a reference, cite accurately the extract you particularly refer to. The assignment would be DUE on early W3 classroom morning. Hand in your plan in font size 12 Times New Roman. The labels are to be in bold letters and in brackets [ ]. Entitle your virtual copy “M** +