[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-207668-en":3,"doc-seo-207668-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},207668,5909887254083,"\tWilliam","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",4,"Exam","Statistics Year 1(AS) - Correlation - Exam Questions","Statistics Year 1(AS) correlation exam questions with worked answer schemes. Tasks cover interpreting a regression line to describe correlation between two variables, stating gradient units, calculating changes over a time interval, and judging the reliability of estimates via interpolation versus extrapolation. Additional questions analyze real-world visibility and humidity data using scatter plots, quartiles, and an outlier definition, plus interpret correlation direction and identify which variable would label the unlabeled axis.","# Statistics Year 1(AS)exam questions\n\nCh.4:Correlation  \nJune 2022 Question 1October 2020 question 2June 2019 question 1June 2018 Question 1  \n3  \n3  \n5  \n8  \n9  \nCh.4:Correlation  \n## June 2022 Question 1\n\n### 1.The relationship between two variables p and t is modelled by the regression line withequation\n\np=22-1.1t  \nThe model is based on observations of the independent variable,t,between 1 and 10  \n(a)Describe the correlation between p and t implied by this model.  \nGiven that p is measured in centimetres and t is measured in days,  \n(b)state the units of the gradient of the regression line.  \nUsing the model,  \n(c)calculate the change in p over a 3-day period.  \nTisam uses this model to estimate the value of pwhen t=19  \n(d)Comment,giving a reason,on the reliability of this estimate.  \n(1)  \n(1)  \n(2)  \n(1)  \n### ANSWER\n\n\n| Qu   | Scheme   | Marks   | AO   |\n| --- | --- | --- | --- |\n| 1.(a)   | Negative (since gradient of regression line is negative)   | B1   | 1.2   |\n|  |  | (1)   |  |\n| (b)   | cm/day(o.e.e.g.cm day⁻¹)   | B1   | 2.2a   |\n|  |  | (1)   |  |\n| (c)   | 3×[±]1.1   | M1   | 3.4  \u003Cbr>1.1b   |\n|  | =decrease of 3.3 [cm]   | A1   |  |\n|  |  | (2)   |  |\n| (d)   | 19 is(well)outside the range [1,10]or involves extrapolation(o.e.)  \u003Cbr>so(possibly)unreliable/inaccurate (o.e.)   | B1   | 2.4  \u003Cbr>s)   |\n|  |  | (1)  \u003Cbr>(5 mark   |  |\n\nVideo solution:  \nhttps://youtu.be/ZtQSYJYy51A  \n## October 2020 question 2\n\n2.Jerry is studying visibility for Camborne using the large data set June 1987.The table below contains two extracts from the large data set  \nIt shows the daily maximum relative humidity and the daily mean visibility.  \n\n| Date   | Daily Maximum  \u003Cbr>Relative Humidity   | Daily Mean Visibility   |\n| --- | --- | --- |\n| Units   | %   |  |\n| 10/06/1987   | 90   | 5300   |\n| 28/06/1987   | 100   | 0   |\n\n(The units for Daily Mean Visibility are deliberately omitted.)  \nGiven that daily mean visibility is given to the nearest 100,  \n(a)write down the range of distances in metres that corresponds to the recorded value 0for the daily mean visibility.  \nJerry drew the following scatter diagram,Figure 2,and calculated some statistics usingthe June 1987 data for Camborne from the large data set.  \n|  | Q   | IQR   |\n| --- | --- | --- |\n| Daily mean visibility   | 1100   | 1600   |\n| Daily maximum relative  \u003Cbr>humidity(%)   | 92   | 8   |\n\nDailymeanvisibilityDaily maximum relative humidity  \nFigure 2  \nJerry defines an outlier as a value that is more than 1.5 times the interquartile rangeabove Q₃or more than 1.5 times the interquartile range belowQ₁.  \n(b)Show that the point circled on the scatter diagram is an outlier for visibility.  \n(c)Interpret the correlation between the daily mean visibility and the daily maximumrelative humidity.  \nArancha Ruiz  \n(1)  \n(2)  \n(1)  \nJerry drew the following scatter diagram,Figure 3,using the June 1987 data forCamborne from the large data set,but forgot to label the x-axis.  \nDaily 4000  \nmean  \nvisibility 3000  \nFigure 3  \n(d)Using your knowledge of the large data set,suggest which variable the x-axis on thisscatter diagram represents.  \n(1)  \nANSWER  \n\n| Question   | Scheme   | Marks   | AOs   |\n| --- | --- | --- | --- |\n| 2(a)   | 0 to 500m   | B1   | 1.2   |\n|  |  | (1)   |  |\n| (b)   | 1100+1600+1.5×1600 [=5100]   | M1   | 2.1   |\n|  | 5300>5100 therefore outlier   | A1   | 1.1b   |\n|  |  | (2)   |  |\n| (c)   | As the humidity increases the mean visibility decreases   | B1   | 2.4   |\n|  |  | (1)   |  |\n| (d)   | (Hours of)sunshine   | B1   | 2.2b   |\n|  |  | (1)   |  |\n| (5marks)   |  |  |  |\n\n## June 2019 question 1\n\n### 1.A sixth form college has 84 students in Year 12 and 56 students in Year 13\n\nThe head teacher selects a stratified sample of 40 students,stratified by year group.  \n(a)Describe how this sample could be taken.  \nThe head teacher is investigating the relationship between the amount of sleep,s hours,that each student had the night before they took an a","cbCaiiej4THh0WgC","https://ap.wps.com/l/cbCaiiej4THh0WgC","pdf",1125770,1,8,"English","en",105,"# Statistics Year 1(AS) exam questions\n## Ch.4:Correlation\n### June 2022 Question 1\n### October 2020 question 2\n### June 2019 question 1\n### June 2018 Question 1","[{\"question\":\"How do you describe the correlation implied by a regression model?\",\"answer\":\"Use the sign of the regression line gradient: a negative gradient implies negative correlation, and a positive gradient implies positive correlation.\"},{\"question\":\"When is an estimate using the regression model considered less reliable?\",\"answer\":\"When the value of the independent variable is outside the observed range (extrapolation), such as estimating at t=19 when observations are between 1 and 10.\"},{\"question\":\"How can you identify outliers using the interquartile range (IQR)?\",\"answer\":\"A point is an outlier if it is more than 1.5×IQR above Q3 or more than 1.5×IQR below Q1.\"}]","Statistics Year 1(AS) - Correlation - Exam Questions | 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