“10 MUST-KNOW STATISTICAL CONCEPTS FOR DATA SCIENTISTS”.

Test

Jugadas 1

Crear copia

Sobre esta actividad

Reading comprehension

Creada por

KATHERINE GISELLE

Colombia

Descarga la versión para jugar en papel

Top 10 resultados

#	Jugador	Acierto	tiempo
1	KATHERINE GISELLE 10 de Junio de 2025	% 83	07:00

¿Quieres aparecer en el Top 10 de este juego? Inicia sesión para identificarte.

Crea tu propio juego gratis desde nuestro creador de juegos

Compite contra tus amigos para ver quien consigue la mejor puntuación en esta actividad

Crear reto

Tipos de sintagmas (II)

idoia rubio

España

(945)

Actividades interactivas para reconocer los distintos tipos de sintagmas
Verbos irregulares en Inglés

Hélmer González Serrano

Colombia

(312)

Se presentan 10 preguntas, cada una con 4 opciones de respuesta. Seleccione la que considere correcta.
Cultura general española

Ernest Serret

España

(100)

Responde las siguientes preguntas
cuanto sabes de Futbol

hugo estay

Chile

(318)

este test esta basado en las diapositivas que pudimos ver con anterioridad, consta de 10 preguntas las cuales tienen alternativas para poder resolverlas.
Brawl stars preguntas

Carlos Andrés Prieto Rodríguez

Colombia

(164)

Completa todas las preguntas


“10 MUST-KNOW STATISTICAL CONCEPTS FOR DATA SCIENTISTS”.Versión en línea Reading comprehension por KATHERINE GISELLE 1 Statistical method modeling the relationship between dependent and independent variables using a linear equation. Choose one or more answers a Linear regression and its assumptions. b P-values1 c Z-tests vs. T-tests d Sampling techniques. 2 Various methods of selecting samples from a population, including Simple Random, Systematic, Convenience, Cluster, and Stratified sampling. a Sampling techniques b Confidence Intervals and Hypothesis Testing c Logistic regression d 3.Z-tests vs. T-tests 3 Statistical hypothesis tests using z-statistic for known population variance or t-statistic for unknown population variance and small sample sizes, respectively. a Z-tests vs. T-tests b P-values1 c Logistic regression d Sampling techniques 4 Statistical measure indicating the probability of achieving a result as extreme or more extreme than observed, given that the null hypothesis is true. a P-values1 b Sampling techniques c Logistic regression d Linear regression and its assumptions 5 Statistical method predicting the probability of a binary outcome based on independent variables, utilizing a sigmoid function a Logistic regression b P-values1 c Confidence Intervals and Hypothesis Testing d Z-tests vs. T-tests 6 Range of values around an estimated parameter, providing a degree of confidence that the true parameter lies within this range. a Confidence Intervals and Hypothesis Testing b Linear regression and its assumptions c Logistic regression d Sampling techniques

“10 MUST-KNOW STATISTICAL CONCEPTS FOR DATA SCIENTISTS”.Versión en línea

Reading comprehension

por KATHERINE GISELLE

Statistical method modeling the relationship between dependent and independent variables using a linear equation.

Choose one or more answers

Linear regression and its assumptions.

P-values1

Z-tests vs. T-tests

Sampling techniques.

Various methods of selecting samples from a population, including Simple Random, Systematic, Convenience, Cluster, and Stratified sampling.

Sampling techniques

Confidence Intervals and Hypothesis Testing

Logistic regression

3.Z-tests vs. T-tests

Statistical hypothesis tests using z-statistic for known population variance or t-statistic for unknown population variance and small sample sizes, respectively.

Z-tests vs. T-tests

P-values1

Logistic regression

Sampling techniques

Statistical measure indicating the probability of achieving a result as extreme or more extreme than observed, given that the null hypothesis is true.

P-values1

Sampling techniques

Logistic regression

Linear regression and its assumptions

Statistical method predicting the probability of a binary outcome based on independent variables, utilizing a sigmoid function

Logistic regression

P-values1

Confidence Intervals and Hypothesis Testing

Z-tests vs. T-tests

Range of values around an estimated parameter, providing a degree of confidence that the true parameter lies within this range.

Confidence Intervals and Hypothesis Testing

Linear regression and its assumptions

Logistic regression

Sampling techniques

Puedes integrar el juego en un LMS compatible con LTI 1.1 o LTI 1.3 como Canvas, Moodle, o Blackboard. De esta manera podrás guardar las puntuaciones automáticamente en el libro de calificaciones de esa plataforma.

“10 MUST-KNOW STATISTICAL CONCEPTS FOR DATA SCIENTISTS”.

Test

Sobre esta actividad

Creada por

Descarga la versión para jugar en papel

Top juegos

Test

Tipos de sintagmas (II)

Test

Verbos irregulares en Inglés

Test

Cultura general española

Test

cuanto sabes de Futbol

Test

Brawl stars preguntas

“10 MUST-KNOW STATISTICAL CONCEPTS FOR DATA SCIENTISTS”.Versión en línea

por KATHERINE GISELLE

Statistical method modeling the relationship between dependent and independent variables using a linear equation.

Choose one or more answers

Various methods of selecting samples from a population, including Simple Random, Systematic, Convenience, Cluster, and Stratified sampling.

Statistical hypothesis tests using z-statistic for known population variance or t-statistic for unknown population variance and small sample sizes, respectively.

Statistical measure indicating the probability of achieving a result as extreme or more extreme than observed, given that the null hypothesis is true.

Statistical method predicting the probability of a binary outcome based on independent variables, utilizing a sigmoid function

Range of values around an estimated parameter, providing a degree of confidence that the true parameter lies within this range.

		%
	Anónimo	%
		%
		%