ELISA Data Reduction: How to generate a standard curve. A standard curve using linear regression analysis in excel can be used. Enter the Standard concentrations that each OD should represent next to their corresponding OD average.
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Create a standard curve graphical representation using measurement data you've gathered from multiple samples to help determine its substance concentration. While Microsoft Excel does not provide a standard curve chart by default, you can manually create one using the chart tools for a scatter chart. The graph requires some minor changes, including removing the horizontal and vertical guidelines from the plot area. Adding a linear trendline to your scatter chart will effectively create a normal curve line that represents the standard curve of your data.
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Enter the standard samples you are graphing into cells 'A1' and 'A2.' For example, enter 'Concentration' and 'Absorbance.'
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Fill in both columns of the table with the corresponding values for your measurements. For example, enter '9,' '6,' '3.5,' '1.25' and '0.725' into the table for column A, and enter '0.74,' '0.4,' '0.19,' '0.11' and '0.02' into column B.
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Highlight all of the values in the table. For example, drag your mouse from the first value in column A and release over the last value in column B.
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Click on the 'Insert' tab, click the 'Insert Scatter (X, Y) or Bubble Chart' drop-down button in the Charts group and then click 'Scatter.'
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Right-click on one of the chart's horizontal gridlines, click 'Format Gridlines…' and then click the radio button next to 'No Lines' in the Format Major Gridlines panel.
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Click on a vertical gridline to select it, and then click 'No Line' in the Format Major Gridlines panel.
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Right-click on the chart's horizontal axis, and then click 'Format Axis…' Enter the maximum value for your data into the 'Maximum' field under Bounds. For example, enter '10'.
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Right-click on the chart's vertical axis, click 'Format Axis…' and then enter your maximum value for the data into the 'Maximum' field under Bounds. For example, enter '1.0'.
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Right-click on one of the data points on the chart, and then click 'Add Trendline…'
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Click on the 'Design' tab. Click the 'Add Chart Element' drop-down button in the Chart Layouts group followed by 'Axis Titles' and 'Primary Horizontal' to add a horizontal axis title to your chart. Repeat the process and select 'Primary Vertical' to add a vertical axis title.
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Enter titles for each axis. For example, enter 'Absorption' for the vertical axis title and 'Concentration (mg/mL)' for the horizontal axis title.
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Click the 'Add Chart Element' drop-down button in the Chart Layouts of the Design tab. Click 'Chart Title' and then 'Above Chart' to add a title to your chart.
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Enter a title for your chart into the chart's title box. For example, enter 'Protein Standard Curve.'
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Located in Denver, Chad Davis has been writing about technology for more than 10 years. He is a technical writer for information technology and product development. Davis provides grant writing and marketing services to small businesses. He holds a Bachelor of Arts in professional writing from the University of New Mexico.
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Davis, Chad. 'Can You Make Standard Curves in Excel?' Small Business - Chron.com, http://smallbusiness.chron.com/can-make-standard-curves-excel-73718.html. Accessed 24 February 2020.
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Regression lines can be used as a way of visually depicting the relationship between the independent (x) and dependent (y) variables in the graph. A straight line depicts a linear trend in the data (i.e., the equation describing the line is of first order. For example, y = 3x + 4. There are no squared or cubed variables in this equation). A curved line represents a trend described by a higher order equation (e.g., y = 2x2 + 5x - 8). It is important that you are able to defend your use of either a straight or curved regression line. That is, the theory underlying your lab should indicate whether the relationship of the independent and dependent variables should be linear or non-linear.
In addition to visually depicting the trend in the data with a regression line, you can also calculate the equation of the regression line. This equation can either be seen in a dialogue box and/or shown on your graph. How well this equation describes the data (the 'fit'), is expressed as a correlation coefficient, R2 (R-squared). The closer R2 is to 1.00, the better the fit. This too can be calculated and displayed in the graph.
The data below was first introduced in the basic graphing module and is from a chemistry lab investigating light absorption by solutions. Beer's Law states that there is a linear relationship between concentration of a colored compound in solution and the light absorption of the solution. This fact can be used to calculate the concentration of unknown solutions, given their absorption readings. This is done by fitting a linear regression line to the collected data.
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