{"id":429,"date":"2025-07-15T13:34:46","date_gmt":"2025-07-15T13:34:46","guid":{"rendered":"https:\/\/functiontranslator.com\/2021\/02\/12\/steyx\/"},"modified":"2021-02-13T11:36:31","modified_gmt":"2021-02-13T11:36:31","slug":"steyx","status":"publish","type":"post","link":"https:\/\/functiontranslator.com\/en\/steyx\/","title":{"rendered":"STEYX"},"content":{"rendered":"

Today, we’ll delve into the capabilities of the STEYX function, a robust statistical tool available in both Microsoft Excel and Google Sheets. STEYX is designed to compute the standard error of the predicted y-value for each x in your dataset’s regression. This allows for a clearer assessment of the accuracy of the linear regression model in representing the data points.<\/p>\n

Syntax<\/h2>\n

The syntax for the STEYX function is consistent across both Excel and Google Sheets:<\/p>\n

=STEYX(known_y's, known_x's)<\/code><\/pre>\n
    \n
  • known_y's<\/code>: This parameter requires an array or range containing the dependent values (y-values).<\/li>\n
  • known_x's<\/code>: This parameter requires an array or range containing the independent values (x-values).<\/li>\n<\/ul>\n
    Example Tasks<\/h2>\n
    Calculating Standard Error<\/h2>\n
    A typical application of the STEYX function is to calculate the standard error of the predicted y-values in a linear regression model. Here is an example using Excel:<\/p>\n\n\n\n\n\n\n\n
    X (Independent)<\/th>\nY (Dependent)<\/th>\n<\/tr>\n
    1<\/td>\n2<\/td>\n<\/tr>\n
    2<\/td>\n4<\/td>\n<\/tr>\n
    3<\/td>\n5<\/td>\n<\/tr>\n
    4<\/td>\n4<\/td>\n<\/tr>\n
    5<\/td>\n6<\/td>\n<\/tr>\n<\/table>\n
    In this dataset, assume the independent values are in cells A2:A6 and the dependent values are in cells B2:B6. The formula to calculate the standard error would look like this:<\/p>\n
    =STEYX(B2:B6, A2:A6)<\/code><\/pre>\n
    Conclusion<\/h2>\n
    The STEYX function is an invaluable asset for evaluating the precision of regression models. By determining the standard error of the predicted y-values, it provides significant insights into the model’s fit to the data. Excel and Google Sheets equip us with the tools necessary for these sophisticated statistical analyses with simplicity and efficiency.<\/p>\n","protected":false},"excerpt":{"rendered":"
    Returns the standard error of the predicted y-value for each x in the regression<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[203],"tags":[],"class_list":["post-429","post","type-post","status-publish","format-standard","hentry","category-statistical"],"acf":[],"yoast_head":"\nExcel STEYX Function \u2013 How It Works, Formula Examples and Syntax<\/title>\n<meta name=\"description\" content=\"Learn what the Excel STEYX function does. 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