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It is used when the worksheet asks for the equation of a line that best fits the given data.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},523421,1791753817,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":19,"category_name":20,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":19,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":52,"preview_page_count":4},962090760730,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","Kuta Software-Infinite Pre-Algebra Scatter Plots  \nName  Date  Period   \nState if there appears to be a positive correlation, negative correlation, or no correlation. When there is a correlation, identify the relationship as linear or nonlinear.  \n1)  \n􀀗􀀓􀀓􀀓􀀓􀀓􀀓  \n􀀖􀀓􀀓􀀓􀀓􀀓􀀓􀀕􀀓􀀓􀀓􀀓􀀓􀀓􀀔􀀓􀀓􀀓􀀓􀀓􀀓  \n3) 􀀗􀀓􀀓􀀓􀀖􀀘􀀓􀀓  \n􀀖􀀓􀀓􀀓  \n􀀕􀀘􀀓􀀓  \n􀀕􀀓􀀓􀀓  \n􀀔􀀘􀀓􀀓  \n􀀔􀀓􀀓􀀓  \n􀀘􀀓􀀓  \n􀀕􀀓􀀓 􀀗􀀓􀀓 􀀙􀀓􀀓 􀀛􀀓􀀓  \n5) 􀀔􀀗􀀓􀀓􀀓􀀓􀀓􀀓􀀔􀀕􀀓􀀓􀀓􀀓􀀓􀀓  \n􀀔􀀓􀀓􀀓􀀓􀀓􀀓􀀓􀀛􀀓􀀓􀀓􀀓􀀓􀀓􀀙􀀓􀀓􀀓􀀓􀀓􀀓􀀗􀀓􀀓􀀓􀀓􀀓􀀓􀀕􀀓􀀓􀀓􀀓􀀓􀀓  \n􀀕 􀀗 􀀙 􀀛 􀀔􀀓  \n2)  \n􀀔  \n􀀓􀀑􀀛  \n􀀓􀀑􀀙  \n􀀓􀀑􀀗  \n􀀓􀀑􀀕  \n4) 􀀚􀀓􀀓􀀓􀀙􀀓􀀓􀀓  \n􀀘􀀓􀀓􀀓  \n􀀗􀀓􀀓􀀓  \n􀀖􀀓􀀓􀀓  \n􀀕􀀓􀀓􀀓  \n􀀔􀀓􀀓􀀓  \n􀀗􀀓􀀓􀀓 􀀛􀀓􀀓􀀓  \n6) 􀀔􀀓  \n􀀛  \n􀀙  \n􀀗  \n􀀕  \n􀀔 􀀕 􀀖 􀀗 􀀘 􀀙 􀀚 􀀛 􀀜  \nConstruct a scatter plot.  \n7)  \n\n| X | Y |\n| --- | --- |\n| 300 | 1 |\n| 800 | 1 |\n| 1,100 | 2 |\n| 1,600 | 2 |\n| 1,700 | 2 |\n\n\n| X | Y |\n| --- | --- |\n| 1,800 | 3 |\n| 3,400 | 3 |\n| 4,700 | 4 |\n| 6,000 | 4 |\n| 8,500 | 6 |\n\n􀀕􀀓􀀓􀀓 􀀗􀀓􀀓􀀓 􀀙􀀓􀀓􀀓 􀀛􀀓􀀓􀀓  \n8)  \n\n| X | Y |\n| --- | --- |\n| 0.1 | 7.5 |\n| 0.1 | 7.6 |\n| 0.3 | 4.5 |\n| 0.4 | 3.2 |\n\n\n| X | Y |\n| --- | --- |\n| 0.4 | 3.3 |\n| 0.6 | 1.4 |\n| 0.6 | 1.7 |\n\n\n| X | Y |\n| --- | --- |\n| 0.6 | 1.8 |\n| 0.9 | 1.5 |\n| 1 | 1.7 |\n\n\n| 􀀛 |  |  |  |  |  |  |  |  |  |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀚 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀙 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀘 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀗 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀖 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀕 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀔 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n\n􀀓􀀑􀀕 􀀓􀀑􀀗 􀀓􀀑􀀙 􀀓􀀑􀀛 􀀔  \nConstruct a scatter plot. Find the slope-intercept form of the equation of the line that best fits the data.  \n9)  \n\n| X | Y |\n| --- | --- |\n| 10 | 700 |\n| 10 | 800 |\n| 30 | 400 |\n| 30 | 500 |\n\nX  \nY  \n\n| X | Y |\n| --- | --- |\n| 70 | 100 |\n| 80 | 100 |\n| 100 | 200 |\n\n\n|  |  |\n| --- | --- |\n| 40 | 300 |\n| 60 | 200 |\n| 70 | 100 |\n\n􀀔􀀓 􀀕􀀓 􀀖􀀓 􀀗􀀓 􀀘􀀓 􀀙􀀓 􀀚􀀓 􀀛􀀓 􀀜􀀓 􀀔􀀓􀀓  \n10) X  Y   X  Y   X  Y  1 20   5 70   7  80  2 40   6  80   9  80  3  50   7  80   10  80 4 60  \n􀀔 􀀕 􀀖 􀀗 􀀘 􀀙 􀀚 􀀛 􀀜 􀀔􀀓  \nKuta Software-Infinite Pre-Algebra Scatter Plots  \nName  Date  Period   \nState if there appears to be a positive correlation, negative correlation, or no correlation. When there is a correlation, identify the relationship as linear or nonlinear.  \n1)  \n􀀗􀀓􀀓􀀓􀀓􀀓􀀓  \n􀀖􀀓􀀓􀀓􀀓􀀓􀀓􀀕􀀓􀀓􀀓􀀓􀀓􀀓􀀔􀀓􀀓􀀓􀀓􀀓􀀓  \nPositive correlation Nonlinear  \n3) 􀀗􀀓􀀓􀀓􀀖􀀘􀀓􀀓  \n􀀖􀀓􀀓􀀓  \n􀀕􀀘􀀓􀀓  \n􀀕􀀓􀀓􀀓  \n􀀔􀀘􀀓􀀓  \n􀀔􀀓􀀓􀀓  \n􀀘􀀓􀀓  \n􀀕􀀓􀀓 􀀗􀀓􀀓 􀀙􀀓􀀓 􀀛􀀓􀀓  \nPositive correlation Linear  \n5) 􀀔􀀗􀀓􀀓􀀓􀀓􀀓􀀓􀀔􀀕􀀓􀀓􀀓􀀓􀀓􀀓  \n􀀔􀀓􀀓􀀓􀀓􀀓􀀓􀀓􀀛􀀓􀀓􀀓􀀓􀀓􀀓􀀙􀀓􀀓􀀓􀀓􀀓􀀓􀀗􀀓􀀓􀀓􀀓􀀓􀀓􀀕􀀓􀀓􀀓􀀓􀀓􀀓  \n􀀕 􀀗 􀀙 􀀛 􀀔􀀓  \nNegative correlation Nonlinear  \n2)  \n􀀔  \n􀀓􀀑􀀛  \n􀀓􀀑􀀙  \n􀀓􀀑􀀗  \n􀀓􀀑􀀕  \n􀀕􀀓􀀓 􀀗􀀓􀀓 􀀙􀀓􀀓 􀀛􀀓􀀓  \nNo correlation  \n4) 􀀚􀀓􀀓􀀓􀀙􀀓􀀓􀀓  \n􀀘􀀓􀀓􀀓  \n􀀗􀀓􀀓􀀓  \n􀀖􀀓􀀓􀀓  \n􀀕􀀓􀀓􀀓  \n􀀔􀀓􀀓􀀓  \n􀀗􀀓􀀓􀀓 􀀛􀀓􀀓􀀓  \nNegative correlation Linear  \n6) 􀀔􀀓  \n􀀛  \n􀀙  \n􀀗  \n􀀕  \n􀀔 􀀕 􀀖 􀀗 􀀘 􀀙 􀀚 􀀛 􀀜  \nNo correlation  \nConstruct a scatter plot.  \n7)  \n\n| X | Y |\n| --- | --- |\n| 300 | 1 |\n| 800 | 1 |\n| 1,100 | 2 |\n| 1,600 | 2 |\n| 1,700 | 2 |\n\n\n| X | Y |\n| --- | --- |\n| 1,800 | 3 |\n| 3,400 | 3 |\n| 4,700 | 4 |\n| 6,000 | 4 |\n| 8,500 | 6 |\n\n􀀕􀀓􀀓􀀓 􀀗􀀓􀀓􀀓 􀀙􀀓􀀓􀀓 􀀛􀀓􀀓􀀓  \n8)  \n\n| X | Y |\n| --- | --- |\n| 0.1 | 7.5 |\n| 0.1 | 7.6 |\n| 0.3 | 4.5 |\n| 0.4 | 3.2 |\n\n\n| X | Y |\n| --- | --- |\n| 0.4 | 3.3 |\n| 0.6 | 1.4 |\n| 0.6 | 1.7 |\n\n\n| X | Y |\n| --- | --- |\n| 0.6 | 1.8 |\n| 0.9 | 1.5 |\n| 1 | 1.7 |\n\n\n| 􀀛 |  |  |  |  |  |  |  |  |  |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀚 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀙 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀘 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀗 |  |  |  |  |  |  |  |  |  |\n|  |  |  | |  |  |  |  |  |  |\n| 􀀖 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀕 |  |  |  |  | |  |  |  | |\n|  |  |  |  |  |  |  |  |  |  |\n| 􀀔 |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |\n\n􀀓􀀑􀀕 􀀓􀀑􀀗 􀀓􀀑􀀙 􀀓􀀑􀀛 􀀔  \nConstruct a scatter plot. Find the slope-intercept form of th","cbCaiv8K9bvv02fv","https://ap.wps.com/l/cbCaiv8K9bvv02fv","pdf",33464,"English","# Correlation classification\n## Positive, negative, or no correlation\n## Linear vs. nonlinear relationship\n# Scatter plot construction\n## Plot given (X, Y) data\n# Best-fit line\n## Slope-intercept form","[{\"question\":\"How do you decide whether the data shows positive, negative, or no correlation?\",\"answer\":\"Look at the overall direction of the points in the scatter plot: an upward trend suggests positive correlation, a downward trend suggests negative correlation, and no clear trend suggests no correlation.\"},{\"question\":\"What does it mean when the relationship is linear versus nonlinear?\",\"answer\":\"Linear relationships follow a roughly straight-line pattern, while nonlinear relationships follow a curved or irregular pattern rather than a straight line.\"},{\"question\":\"What is the slope-intercept form and when is it used here?\",\"answer\":\"The slope-intercept form expresses the line of best fit as y = mx + b. It is used when the worksheet asks for the equation of a line that best fits the given data.\"}]","Kuta Software-Infinite Pre-Algebra Scatter Plots - Worksheet - Correlation and Scatter Plot Practice | PDF",1791426845]