Processing...

`y = "a" + "b" * x `

Enter a value for all fields

The **Least-squares Trend Inference** calculator computes the value of the dependent variable (**Y**) based on the intercept (**a**), the slope (**b**) and a value of **X**. This is the result of a least-squares trend linear equation, through a set of X and Y values. This is also known as simple linear regression.

**INSTRUCTIONS:** Enter the following:

- (
**a**) Y axis Intercept - (
**b**) Slope of Line - (
**x**) Independent Variable

**Domain (Y):** The calculator returns the value of Y.

The formula for the least-squared regression line is in the following form:

where:

`b = ( (sum(XY) - (sumX * sumY)"/n")) / (sum(X^2) - (sumX)^2"/n") `

and

` a = MY - b*MX` MY is mean of Y. MX is mean of X.

To compute the least squares trend line for a set of values, CLICK HERE.

After you have entered the values in the calculator for a, b and x, the plot function will let you enter a range (min and max) for x and a number of steps. When you enter the range for x and number of steps, it will generate a graph of the line graphing the values of **y** using your entered **a** and **b**, stepping through values of **x** between the range specified.

**Observational Stats**: This function accepts a table of numbers separated by commas and calculates observational statistics for any of the columns. This includes count, min, max, sum, sum of squares (Σx²), square of the sum (Σx)², mean, median, mode, range, mid point, rand, sort up, sort down, rand, population variance, population standard deviation, the sample/experimental variance, sample/experimental standard deviation.**Frequency Distribution**: This function lets you enter a string of numbers separated by commas, a low and high range and a number of bins. It then computes how many of the observations are in each of the bins between the high and low values designated.**Paired Sample t-test**: This computes the various parameters associated with the Paired Sample t-test.**ANOVA (one way)**: The is one way analysis of variance**(χ**This computes the Chi-Square value for an nxm array of data and provides the degrees of freedom.^{2}) Chi-Square Test:**Linear Regression**: This computes the regression line (least-squares) through a set of X and Y observations. It also computes the regression coefficient (r).**y = a + bx**: This is linear equation used with Linear Regression to predict values of Y.**Wilcoxon Signed Rank Test**: This provides the Wilcoxon statistics and critical value for two groups of numeric observations based on an alpha value and whether it's a one or two tailed test.- Slope-Intercept form of a Line based on two points.
- Slope between two points
- Range value based on the slope-intercept formula of a line and a value of the domain.
- Compute the Probability between z SCORES
- College Level Statistics Calculator (Stat Calc).
- Count of Observations in a Set - this is the number (n) of values in a set.
- Minimum Value in a Set - this is the minimum observed value
- Maximum Value in a Set- this is the maximum value in the set.
- Numeric Sort (up and down) - this returns a comma separated list of the observations in ascending or descending order.
- Create a random subset of the a list of numeric values
- Random number from a range you specify
- Frequency distribution of data.
- Σx - this is the sum of the values in a set.
- Σx² - this is the sum of the squared values
- (Σx)² - this is the square of the summed values.
- Mean
- Median - the middle ordered value
- Mode - the most recurring observation
- Mid Point in a Set - this is the mid point of the observation range.
- Range in a Set - this is the difference between the max and the min.
- Population Variance of the values
- Population standard deviation of the values
- Sample Variance of the values
- Sample Standard Deviation of the values
- Compute the z SCORE based on the mean and standard deviation
- Compute the z SCORE in a set of observations
- Compute the percentile of a single observation (y) in a set (X)
- SDOM - standard deviation of mean
- Percent Relative Standard Deviation

- Dowdy, Shirley, and Stanley Wearden. Statistics for Research. N.p.: John Wiley & Sons, n.d. Print.(Chapter 9 Distributions of Paired Variables)