<prompt> Khetha mohlala o utloahalang ho bontsa tlhahiso ea mohlala o bonolo oa mela.nan  <response>: Instruction in English: Select a reasonable example to show the output of a simple linear regression model. . Response in English: Sure! Here is an example of the output of a simple linear regression model.Suppose we have collected data on the number of hours a group of students studied for an exam and their exam scores. We want to know if there is a relationship between the number of study hours and exam scores. To determine this, we can perform a simple linear regression analysis. Lets say our sample data looks like this: Study Hours Exam Score ------ 2 71 3 78 4 85 5 89 6 91 7 95 8 98 After performing the regression analysis, we find that the linear regression equation is:Exam Score 61.50 4.90 Study Hours.This equation tells us that for every additional hour spent studying, we can expect the students exam score to increase by 4.90 points. The intercept value of 61.50 tells us the expected exam score for a student who does not study at all.The linear regression output might also include values such as the R-squared value and the p-value. In this example, lets say the R-squared value is 0.95. This indicates a strong positive correlation between the two variables. The p-value might be reported as 0.001, which is highly statistically significant, indicating that the relationship between study hours and exam scores is not due to chance.In summary, our simple linear regression model tells us that there is a significant positive relationship between the number of hours a student spends studying and their exam score. . Response in Sesotho: Ehlile! Mohlala ke ona oa tlhahiso ea mohlala o bonolo oa mola oa ho khutlisa. A re re re bokeletse lintlha tsa palo ea lihora tseo sehlopha sa liithuti li ithutileng tsona bakeng sa tlhahlobo le lintlha tsa bona tsa tlhahlobo. Re batla ho tseba hore na ho na le kamano pakeng tsa palo ea lihora tsa ho ithuta le lintlha tsa tlhahlobo. Ho tseba sena, re ka etsa tlhahlobo e bonolo ea linear regression. Ha re re data ea rona ea mohlala e shebahala tjena: Lihora tsa ho Ithuta Lintlha tsa tlhahlobo --- 2 71 3 78 4 85 5 89 6 91 7 95 8 98 Ka mora ho etsa tlhahlobo ea ho khutlela morao, re fumana hore tatellano ea mokhoa oa ho khutlela morao ke: Tlhahlobo ea Tlhahlobo 61.50 4.90 Lihora tsa ho Ithuta. Equation ena e re bolella hore bakeng sa hora e ngoe le e ngoe e eketsehileng e sebelisoang ho ithuta, re ka lebella hore lintlha tsa tlhahlobo ea seithuti li eketsehe ka lintlha tse 4.90. Theko ea ho qetela ea 61.50 e re bolella lintlha tsa tlhahlobo tse lebelletsoeng bakeng sa moithuti ea sa ithuteng ho hang. Phaello ea mela e ka nang ea kenyelletsa boleng bo kang R-squared value le p-value. Mohlaleng ona, ha re re boleng ba R-squared ke 0.95. Sena se bontša kamano e matla e ntle pakeng tsa mefuta e meli. The p-value e ka tlalehoa e le 0.001, e leng ea bohlokoa haholo ho latela lipalo-palo, e bontšang hore kamano pakeng tsa lihora tsa ho ithuta le lintlha tsa tlhahlobo ha ea bakoa ka tšohanyetso. Ka bokhutsoane, mohlala oa rona o bonolo oa mokhoa oa ho khutlela morao o re bolella hore ho na le kamano e ntle pakeng tsa palo ea lihora tseo moithuti a li qetang a ithuta le lintlha tsa hae tsa tlhahlobo. 