2/3/2024 0 Comments Weighted average method mapThe statistics are calculated using only the proportion of the lines that are within the boundary. The volume was used to calculate the statistics (sum, minimum, maximum, and average) for the layer. The figure and table below explain the statistical calculations of a line layer within a hypothetical boundary. The results are displayed using unique symbols. Lines do not have to be completely contained within a boundary to be counted toward the mode and each line is counted as one feature, regardless of the proportion that is contained within the boundary. The mode for line layers is based on the count of features that intersect the boundary. The results are displayed using graduated symbols. When summarizing lines, use fields with counts and amounts rather than rates or ratios so proportional calculations make logical sense in your analysis. Line layers are summarized numerically using only the proportions of the line features that are within the input boundary. From the results you can see that District A has 2,568 students and District B has 3,400 students. The calculations and results are given in the table above. The Type field gives the type of school (elementary, middle school, or secondary) and a student population field gives the number of students enrolled at each school. The Population field was used to calculate the numeric statistics (count, sum, minimum, maximum, and average) and the Type field was used for mode.Ī real-life scenario in which this analysis could be used is in determining the total number of students in each school district. The figure and table below explain the statistical calculations of a point layer within a hypothetical boundary. Therefore, none of the calculations are weighted. Point layers are summarized using only the point features within the input boundary. The following equation is used to calculate weighted mean: where: How Spatial Aggregation worksĪverage statistics are calculated using weighted mean for line and area features. Google BigQuery does not support mode calculations. Both input layers must be from the same database connection.Spatial Aggregation using line and area features as the Choose a layer to summarize parameter is not supported for read-only connections.The following limitations apply for Google BigQuery, Snowflake, and database platforms that are not supported out-of-the-box: For datasets from SQL Server, the data must also have the same data type (geography or geometry). When you perform spatial aggregation or spatial filtering on data from the same database connection, you must ensure that all the data is stored in the same spatial reference system. Each time a field is added to the list of summary statistics, a new field will appear below it. The Additional options parameter can be expanded and extra statistics can be assigned. For more information, see How Spatial Aggregation works. From this point, the formula is solved the same way as explained earlier.It is best practice to use numbers rather than rate/ratios when calculating statistics for lines and areas so that the proportional calculations make logical sense. Note the semicolons are now commas, which indicate a horizontal array. We can visualize this operation in cell G5 like this: =SUMPRODUCT( // horizontal array SUMPRODUCT multiplies corresponding elements of the two arrays together, then returns the sum of the product. Looking first at the left side, we use the SUMPRODUCT function to multiply weights by corresponding scores and sum the result: =SUMPRODUCT(weights,C5:E5) // returns 88.25 The formula in cell G5 is: =SUMPRODUCT(weights,C5:E5)/SUM(weights) In the worksheet shown, scores for 3 tests appear in columns C through E, and weights appear in the named range weights (I5:K5). This sounds really boring, but SUMPRODUCT is an incredibly versatile function that shows up in all kinds of useful formulas. In a nutshell, SUMPRODUCT multiplies ranges or arrays together and returns the sum of products. The core of this formula is the SUMPRODUCT function. In Excel, this can be represented with the generic formula below, where weights and values are cell ranges: =SUMPRODUCT(weights,values)/SUM(weights) We can calculate a weighted average by multiplying the values to average by their corresponding weights, then dividing the sum of results by the sum of weights. In other words, some values have more "weight". A weighted average (also called a weighted mean) is an average where some values are more important than others. In this example, the goal is to calculate a weighted average of scores for each name in the table using the weights that appear in the named range weights (I5:K5) and the scores in columns C through E.
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