[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-208343-en":3,"doc-seo-208343-105":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},208343,2336477974920,"Mimi","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",4,"Exam","GCSE (9–1) 数学 - 统计学 - 交付指南 - 第2版","GCSE (9–1) Mathematics Delivery Guide - Statistics provides curriculum-aligned guidance for teaching the statistics component of the specification. It outlines core teaching content and conceptual development through three linked strands: sampling, interpreting and representing data, and analysing data. The guide emphasizes descriptive versus inferential statistics, sampling bias and variability, correct graphical interpretation, summary measures and their limitations, and understanding correlation versus causation when working with bivariate data.","Qualification Accredited  \nGCSE (9–1) Delivery Guide  \nMATHEMATICS  \nJ560 For first teaching in 2015  \nStatistics  \nVersion 2  \n[www.ocr.org.uk/maths](www.ocr.org.uk/maths)  \nIntroduction  \nGCSE (9–1) Mathematics Delivery Guide  \nGCSE (9–1)  \nMATHEMATICS  \nDelivery guides are designed to represent a body of knowledge about teaching a particular topic and contain:  \n• Content: A clear outline of the content covered by the delivery guide;  \n• Thinking Conceptually: Expert guidance on the key concepts involved, common difficulties students may have, approaches to teaching that can help students understand these concepts and how this topic links conceptually to other areas of the subject;  \n• Thinking Contextually: A range of suggested teaching activities using a variety of themes so that different activities can be selected which best suit particular classes, learning styles or teaching approaches.  \nIf you have any feedback on this Delivery Guide or suggestions for other resources you would like OCR to develop, please email [resources.feedback@ocr.org.uk](resources.feedback@ocr.org.uk)  \nCurriculum content Thinking conceptually  \nThinking contextually  \nLearner resources  \nPage 3  \nPage 5  \nPage 6  \nPage 8  \n2 © OCR 2016  \nCurriculum content  \nGCSE (9–1) Mathematics Delivery Guide  \n\n| GCSE (9–1)\u003Cbr>content Ref. | Subject content | Initial learning for this qualification will enable learners to  | Foundation tier learners should also be able to… | Higher tier learners should additionally be able to… | DfE\u003Cbr>Ref. |\n| --- | --- | --- | --- | --- | --- |\n| OCR 12 | Statistics |  |  |  |  |\n| 12.01 | Sampling |  |  |  |  |\n| 12.01a | Populations and samples |  | Define the population in a study, and understand the difference between population and sample. Infer properties of populations or distributions from a sample.\u003Cbr>Understand what is meant by simple random sampling, and bias in sampling. |  | S1 |\n| 12.02 | Interpreting and representing data |  |  |  |  |\n| 12.02a | Categorical and numerical data | Interpret and construct charts appropriate to the data type; including frequency tables, bar charts, pie charts and pictograms for categorical data, vertical line charts for ungrouped discrete numerical data.\u003Cbr>Interpret multiple and composite bar charts. | Design tables to classify data. Interpret and construct line graphs for time series data, and identify trends (e. g. seasonal variations) . |  | S2 |\n| 12.02b | Grouped data |  |  | Interpret and construct diagrams for grouped data as appropriate, i. e. cumulative frequency graphs and histograms (with either equal or unequal class intervals) . | S3\u003Cbr>S4 |\n\n3 © OCR 2016  \nCurriculum content  \nGCSE (9–1) Mathematics Delivery Guide  \n\n| GCSE (9–1)\u003Cbr>content Ref. | Subject content | Initial learning for this qualification will enable learners to  | Foundation tier learners should also be able to… | Higher tier learners should additionally be able to… | DfE\u003Cbr>Ref. |\n| --- | --- | --- | --- | --- | --- |\n| 12.03 | Analysing data |  |  |  |  |\n| 12.03a | Summary statistics | Calculate the mean, mode, median\u003Cbr>and range for ungrouped data.\u003Cbr>Find the modal class, and calculate estimates of the range, mean and median for grouped data, and understand why they are estimates. Describe a population using statistics. Make simple comparisons.\u003Cbr>Compare data sets using ‘like for like’summary values.\u003Cbr>Understand the advantages and disadvantages of summary values. |  | Calculate estimates of mean, median, mode, range, quartiles and interquartile range from graphical representation of grouped data.\u003Cbr>Draw and interpret box plots. Use the median and interquartile range to compare distributions. | S4,\u003Cbr>S5 |\n| 12.03b | Misrepresenting data | Recognise graphical misrepresentation through incorrect scales, labels, etc. |  |  | S4 |\n| 12.03c | Bivariate data | Plot and interpret scatter diagrams for bivariate data.\u003Cbr>Recognise correlation. | Interpret correlation within the context of the v","cbCaij7kTMg5yZVi","https://ap.wps.com/l/cbCaij7kTMg5yZVi","pdf",3911813,1,16,"English","en",105,"# Introduction\n## Delivery guide purpose and structure\n# Curriculum content\n## Sampling\n## Interpreting and representing data\n## Analysing data\n## Summary statistics\n## Misrepresenting data\n## Bivariate data\n## Outliers","[{\"question\":\"What are the three broad areas of statistics content covered in the guide?\",\"answer\":\"The guide structures statistics teaching into sampling, interpreting and representing data, and analysing data.\"},{\"question\":\"How does the guide distinguish descriptive statistics from inferential statistics?\",\"answer\":\"Descriptive statistics use graphs and summary measures to convey information about available data, while inferential statistics use samples to make deductions and conclusions about the population.\"},{\"question\":\"What key issues does the guide highlight when interpreting data?\",\"answer\":\"It stresses recognizing misrepresentation from incorrect scales or labels, understanding limitations of summary values, and distinguishing correlation from causation for bivariate data.\"}]","GCSE (9–1) 数学 - 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