Sentences with phrase «ordinary least squares»

Applying simple linear regression using ordinary least squares to the data shows that this trend is statistically significant at the 95 per cent level.

For example, one can use robust regression or ordinary least squares for the estimation.

For instance, ordinary least squares regression is used properly less than 20 % of the time in sell - side research, in my opinion.

We conducted negative binomial regression analysis instead of ordinary least squares regression analysis because accuracy of surrogate estimation was a count variable displaying overdispersion (i.e., its variance is larger than its mean).

They compare quantile regression results to those from a conventional Ordinary Least Squares (OLS) model (which focuses on distribution averages).

«Three beliefs about God were tested separately in ordinary least squares regression models to predict five classes of psychiatric symptoms: general anxiety, social anxiety, paranoia, obsession, and compulsion,» reads the abstract for this paper.

Specifically, we estimate curriculum effects using kernel matching, common - support - restricted ordinary least squares (restricted OLS), and remnant - based residualized matching.

The slope of the trend line (from ordinary least squares) is only 0.03 deg.C / decade.

Lagged Ordinary Least Squares multiple regression techniques were utilized to examine the link between perpetration of dating violence and school factors.

For both datasets, the trends are computed using the method of ordinary least squares.

For the measurements of each weather balloon, we calculated the best linear fit for each of the regions (using a statistical technique known as «ordinary least squares linear regression»).

I used ordinary least squares regression covering a data set of 4,604 companies.

In their February 2017 paper entitled «Bayesian Model Averaging, Ordinary Least Squares and the Price of Gold», Dirk Baur and Brian Lucey analyze a large set of factors that potentially influence the price of gold via two methods: Ordinary Least Squares (OLS, scatter plot) and Bayesian Model Averaging (BMA, accounting for model uncertainty).

Because respondents were randomly assigned to receive the refutation text or the control, we use straightforward analyses including descriptive statistics, t - tests, and ordinary least squares regressions.

A bivariate analysis to illustrate the relationship between variables was conducted, along with an ordinary least squares regression to look for predictors of skill level and diversity of Web usage while controlling for various social and use context factors.

Ordinary least squares regression was used to calculate how sensitive unemployment rates were in each state relative to overall US unemployment rates.

(Note: this is an ordinary least squares regression.

If you've ever taken a statistics or econometrics course, you might recognize the calculation and application of the left - inverse as the ordinary least squares (OLS) estimation of the weights; that means that in this case, «closest» implies that the weights we found minimize the sum of the squares of the differences («errors» or «residuals») between our replicated portfolio and VTSMX.

Because temperature data violates one of the assumptions of Ordinary Least Squares (OLS) regression - that all the data are independent observations.

The ordinary least squares (OLS) regression approach used will, however, underestimate Y in the presence of fluctuations in surface temperature that do not give rise to changes in net radiative flux fitting the linear model.

The impact of climate change on output is examined in this study using the ordinary least squares (OLS) method.

The Household Income and Expenditure Survey 2010 (HIES, 2010) data have been used to estimate the Ordinary Least Square (OLS) regressions for examining the impact.

This correlation structure approximates the results of an ordinary least squares regression while ignoring the lack of independence among the observations.

Analyses were conducted using PROCESS, a conditional modeling macro that uses an ordinary least squares - based path analytical framework to test for both direct and indirect effects [31].

Ordinary least square regression results indicate that children whose parents reported that they or one of their parents had PTE exposure had significantly higher levels of externalizing and internalizing behavior with effect sizes (Cohen's d) ranging from 0.18 to 0.45.

The hypotheses were evaluated by multiple regression analyses using ordinary least squares.