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𝐎𝐃𝐔𝐔 𝐆𝐀𝐌𝐌𝐀𝐂𝐇𝐈𝐈𝐒𝐀𝐀

𝑪𝒉𝒂𝒂𝒏𝒂𝒂𝒍𝒐𝒕𝒂 𝑨𝒇𝒂𝒂𝒏 𝑶𝒓𝒐𝒎𝒐𝒐𝒕𝒊𝒊𝒏 𝑩𝒂𝒓𝒔𝒊𝒊𝒔𝒐𝒐𝒇𝒊𝒊 𝑩𝒂𝒔𝒉𝒂𝒏𝒏𝒂𝒏𝒔𝒊𝒊𝒔𝒐𝒐 𝑻𝒂'𝒂𝒏 𝑰𝒔𝒊𝒏𝒊𝒊𝒇 𝑸𝒂𝒃𝒂𝒏𝒏𝒆𝒆 𝑫𝒉𝒖𝒇𝒏𝒆𝒆𝒓𝒓𝒂𝒂 𝑲𝒂𝒏𝒂𝒂𝒇𝒖𝒖 𝑪𝒉𝒂𝒂𝒏𝒂𝒂𝒍𝒐𝒕𝒂 𝑨𝒇𝒂𝒂𝒏 𝑶𝒓𝒐𝒎𝒐𝒐𝒕𝒊𝒊𝒏 𝑩𝒂𝒓𝒔𝒊𝒊𝒔𝒂𝒏 𝑰𝒔𝒊𝒏𝒊𝒊𝒇 𝑸𝒂𝒃𝒂𝒏𝒏𝒆𝒆 𝑫𝒉𝒖𝒇𝒏𝒆𝒆𝒓𝒓𝒂𝒂 𝑲𝒂𝒏𝒂𝒂𝒇𝒖𝒖 𝑱𝒐𝒊𝒏 𝑮𝒐𝒅𝒉𝒖𝒖𝒅𝒉𝒂𝒂𝒏 𝑵𝒖 𝑯𝒐𝒓𝒅𝒐𝒇𝒂𝒂.

𝐇𝐮𝐛𝐚𝐜𝐡𝐢𝐢𝐬𝐚: 𝑪𝒉𝒂𝒂𝒏𝒂𝒂𝒍𝒊𝒊 𝑨𝒇𝒂𝒂𝒏 𝑶𝒓𝒐𝒎𝒐𝒐 𝑻𝒂'𝒂𝒏 3𝑲 𝒇𝒊 𝑰𝒔𝒂𝒂 𝑾𝒐𝒍𝒊𝒊𝒏 𝑲𝒂𝒏 𝑯𝒐𝒋𝒋𝒂𝒏𝒏𝒖 𝑻𝒂'𝒂𝒂 𝑲𝒂𝒏𝒂𝒂𝒇𝒖𝒖 𝑵𝒂𝒎𝒏𝒊 𝑵𝒖𝒕𝒕𝒊 𝑫𝒂𝒃𝒂𝒍𝒂𝒎𝒖𝒖 𝑭𝒆𝒆𝒕𝒂𝒏 𝑨𝒔𝒊𝒊𝒏 𝑵𝒖 𝑸𝒖𝒏𝒏𝒂𝒎𝒂𝒂

𝐂𝐡𝐚𝐧𝐧𝐞𝐥 𝐀𝐟𝐚𝐚𝐧 𝐎𝐫𝐨𝐦𝐨𝐨 𝐐𝐨𝐟𝐚 3𝐊+
𝐅𝐫𝐞𝐞 𝐏𝐫𝐨𝐦𝐨𝐭𝐞𝐫: @Rafiiqul_Islaam2

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𝐂𝐡𝐚𝐚𝐧𝐚𝐚𝐥𝐢𝐢 𝐚𝐤𝐤𝐚𝐦𝐢𝐢 𝐛𝐚𝐫𝐛𝐚𝐚𝐝𝐝𝐮𝐮?
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𝐔𝐦𝐫𝐢𝐢𝐧 𝐊𝐞𝐞 𝐌𝐞𝐞𝐪𝐚𝐚?

𝐅.𝐖: @Rafiqul_Islaam

𝐎𝐃𝐔𝐔 𝐆𝐀𝐌𝐌𝐀𝐂𝐇𝐈𝐈𝐒𝐀𝐀!!

𝐍𝐚𝐦𝐨𝐨𝐧𝐧𝐢 𝐈𝐝𝐝𝐨𝐨 𝐉𝐢𝐫𝐭𝐚𝐧 𝐓𝐞𝐞𝐬𝐬𝐚𝐧𝐢𝐢 𝐁𝐞𝐞𝐤𝐬𝐢𝐬𝐚𝐚𝐰𝐰𝐚𝐧 𝐆𝐚𝐫𝐚𝐚 𝐆𝐚𝐫𝐚𝐚 𝐇𝐨𝐫𝐝𝐨𝐟𝐮𝐮𝐧 𝐇𝐨𝐣𝐢𝐢 𝐀𝐫𝐠𝐚𝐜𝐡𝐮𝐮 𝐁𝐚𝐫𝐛𝐚𝐚𝐝𝐝𝐚𝐧 𝐂𝐡𝐚𝐧𝐧𝐞𝐥 𝐊𝐚𝐧𝐚 𝐈𝐫𝐫𝐚𝐭𝐭𝐢 𝐁𝐞𝐞𝐤𝐬𝐢𝐬𝐚 𝐆𝐮𝐲𝐲𝐚𝐚 𝐆𝐮𝐲𝐲𝐚𝐚𝐧 𝐁𝐚𝐡𝐮 𝐇𝐨𝐫𝐝𝐨𝐟𝐚𝐚

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𝐅𝐫𝐞𝐞 𝐖𝐚𝐯𝐞𝐫: @Rafiqul_Islaam

Violations of the assumptions of regression analysis can lead to misleading results and interpretations. Here are some common violations, their causes and consequences, along with remedial measures:

▎1. Linearity

• Cause: The relationship between the independent and dependent variables is not linear.

• Consequences: The model may underestimate or overestimate the effect of predictors, leading to biased coefficients.

• Remedial Measures:

• Transform variables (e.g., log, square root).

• Use polynomial regression or interaction terms.

• Consider non-linear models (e.g., generalized additive models).

▎2. Independence of Errors

• Cause: Errors are correlated (e.g., in time series data).

• Consequences: Underestimation of standard errors, leading to inflated t-statistics and false significance.

• Remedial Measures:

• Use time series methods (e.g., ARIMA).

• Add lagged variables to the model.

• Employ Generalized Least Squares (GLS) or robust standard errors.

▎3. Homoscedasticity

• Cause: Variance of errors is not constant across all levels of the independent variable(s).

• Consequences: Standard errors may be biased, affecting hypothesis tests and confidence intervals.

• Remedial Measures:

• Use weighted least squares (WLS).

• Transform the dependent variable.

• Check for outliers that may affect variance.

▎4. Normality of Errors

• Cause: Errors are not normally distributed, especially in small samples.

• Consequences: Violated assumptions can affect the validity of hypothesis tests and confidence intervals.

• Remedial Measures:

• Use transformations (e.g., log or Box-Cox).

• Consider robust regression techniques.

• Increase sample size if possible.

▎5. No Multicollinearity

• Cause: High correlation among independent variables.

• Consequences: Inflated standard errors, making it difficult to determine the effect of individual predictors.

• Remedial Measures:

• Remove or combine correlated predictors.

• Use ridge regression or principal component analysis (PCA).

• Center variables to reduce multicollinearity.

▎6. No Autocorrelation

• Cause: Errors are correlated across observations, often in time series data.

• Consequences: Underestimation of standard errors, leading to unreliable hypothesis tests.

• Remedial Measures:

• Use Durbin-Watson test to detect autocorrelation.

• Incorporate lagged variables.

• Use autoregressive models.

▎Conclusion

To ensure the validity of regression analysis, it's crucial to check for these assumptions before interpreting results. If violations are detected, appropriate remedial measures should be taken to improve the model's reliability and accuracy. Regular diagnostic checks and visualizations (like residual plots) can help identify potential issues early in the analysis process.

Cause and consequences of violations assumptions of regression analysis with remedial measures

𝐂𝐡𝐚𝐚𝐧𝐚𝐚𝐥𝐢𝐢 𝐚𝐤𝐤𝐚𝐦𝐢𝐢 𝐛𝐚𝐫𝐛𝐚𝐚𝐝𝐝𝐮𝐮?
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https://t.me/+0puaGJwLzLgyY2U8
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Chaanaalii Ajaa'ibaa kana isiniif qabannee dhufneerraa join gochuudhaan erga inni qabu akka irraa fayyadamnuu

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𝐅.𝐖: @Rafiqul_Islaam

𝐂𝐡𝐚𝐚𝐧𝐚𝐚𝐥𝐢𝐢 𝐚𝐤𝐤𝐚𝐦𝐢𝐢 𝐛𝐚𝐫𝐛𝐚𝐚𝐝𝐝𝐮𝐮?
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𝐅𝐫𝐞𝐞 𝐖𝐚𝐯𝐞𝐫: @Rafiqul_Islaam

𝐇𝐨𝐰 𝐎𝐥𝐝 𝐀𝐫𝐞 𝐘𝐨𝐮?
𝐔𝐦𝐫𝐢𝐢𝐧 𝐊𝐞𝐞 𝐌𝐞𝐞𝐪𝐚𝐚?

𝐅.𝐖: @Rafiqul_Islaam

𝐂𝐡𝐚𝐚𝐧𝐚𝐚𝐥𝐢𝐢 𝐚𝐤𝐤𝐚𝐦𝐢𝐢 𝐛𝐚𝐫𝐛𝐚𝐚𝐝𝐝𝐮𝐮?
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