Sentence examples for make generalised from inspiring English sources

Yes, but only marginally, and the overlap is so great as to make generalised gender-based judgments useless.

Due to the requirement to make generalised BCSA transceive beamforming also suitable for non-regenerative MGMW relaying with multicasting strategy, it has a slight difference to [3, 10, 16].

Another limitation was that using assessment results for only one year of study may not be sufficient to make generalised statements about the performance of international medical students across different assessment instruments.

Furthermore, our experiments were carried out using canine derived cells and it may not be possible to make generalised statements about the activity of curcumin on MSC-like cells in other species.

ED Oh, I completely agree that making generalised gender assumptions about how women are and how men are, as if they're some giant single-cell globule, is pretty unhelpful.

If we wish to conduct research that is focussed on a very specific problem, and are not concerned with making generalised moral claims, we need a method that will accommodate this narrow focus.

The analysis included four steps: (i) reading the material to obtain an overall impression and bracketing previous preconceptions; (ii) identifying units of meaning representing different aspects of experiences with the program, and coding for these; (iii) condensing and summarizing contents of each coded group; and (iv) making generalised descriptions regarding experiences with the program.

Hunt tweeted: "On BBC QT I was trying to make a generalised point about the use of unqualified teachers in schools.

"To make such generalised statements creates further divide between Black and White Australians and we're still trying to cope with forming some kind of reconciliation as a country," protest organiser Lynda-June Coe told VICE.

Indeed, it has recently been pointed out in a Cochrane review that heterogeneity in study comparison groups, outcomes and measures makes it difficult to draw generalised conclusions on effects of pharmacist interventions.

For secondary continuous outcomes, variations between control and intervention groups will be investigated using the t-test and, if necessary, covariate adjustment made using generalised linear models (to include strata affects); for secondary binary outcomes, differences will be compared using chi-squared tests and, if necessary, logistic regression.