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Analyzing Zona Column and Frequency Table in Climatologia Data

1) Obtener la tabla de frecuencias completa para la Zona y completar las siguientes frases:

La variable "Zona" es de tipo:

Summary of Frequency Table for 'Zona'

  • Type of Variable: Categorical (Nominal)
  • Categories and their Frequencies:
    • Norte: 21
    • Centro: 15
    • Sur: 13

De las _ ciudades estudiadas, hay _. en la zona Sur, representando un _ del total, El _% de las ciudades no están en la zona Norte

To complete the sentences, we need to calculate the total number of cities, the percentage of cities in the Sur zone, and the percentage of cities not in the Norte zone. Let's compute these values.

Summary of City Distribution by Zone

  • Total Cities Studied: 49
  • Cities in the Sur Zone: 13, representing 26.53% of the total.
  • Percentage of Cities Not in the Norte Zone: 57.14%

Indicar cuál es la medida de posición central más adecuada para esta variable y comentaría.

For the variable 'Zona', which is categorical and nominal, the most appropriate measure of central tendency is the mode. This is because the mode identifies the most frequently occurring category within the data, which is useful for understanding the most common zone among the cities studied.

La media aritmética de las temperaturas es _ y su media geométrica vale _

To find the arithmetic mean and geometric mean of the temperatures, we'll calculate these values using the appropriate statistical functions.

Summary of Temperature Statistics

  • Arithmetic Mean of Temperatures: 15.72°C
  • Geometric Mean of Temperatures: 15.51°C

La mitad de las ciudades tienen unas precipitaciones de _ o menos. El nombre del estadistico calculado es _. Tipo de medida _.

To find the value below which half of the cities have their precipitation, we'll calculate the median. The median is a measure of central tendency that divides the data into two equal halves.

Summary of Precipitation Statistics

  • Median Precipitation: 500.4 mm
  • Name of the Statistic: Median
  • Type of Measure: Position

El percentil 37 de las precipitaciones es _. Indicar su significado: _

To find the 37th percentile of precipitation, we'll calculate this value which indicates that 37% of the data falls below this point. This helps in understanding the distribution of precipitation across the dataset.

Summary of Precipitation Percentile

  • 37th Percentile of Precipitations: 460.84 mm
Significance: This value indicates that 37% of the cities have annual precipitation amounts of 460.84 mm or less. It is a measure of distribution that helps to understand how precipitations are spread among the cities.

La temperatura de estas ciudades oscila entre los _ de _ (ciudad) y los _ de_ (ciudad), lo que supone un rango de temperaturas de _.

Temperature Range Across Cities

  • Lowest Temperature: 10.6°C in Castellón
  • Highest Temperature: 20.8°C in Las Palmas
  • Temperature Range: 10.2°C

La precipitación media es _, con una desviación tipica muestral de _. Estudiar si la media anterior es representativa, utilizando para ello el

estadístico adecuado: _

Mean and Standard Deviation of Precipitations

  • Mean Precipitation: 577.77 mm
  • Standard Deviation: 306.46 mm
To determine if the mean is representative, we can calculate the coefficient of variation, which is the ratio of the standard deviation to the mean. This statistic helps assess the level of dispersion relative to the mean.

Analysis of Mean Precipitation Representativeness

  • Coefficient of Variation (CV): 0.53
Interpretation: A CV greater than 0.1 generally indicates a high level of variability relative to the mean. In this case, the CV of 0.53 suggests that the mean precipitation is not very representative due to significant variability in the data.

Además, en el intervalo [_, _] se encuentran aproximadamente el 95% de las precipitaciones, aunque en realidad se encuentran el _.

Confidence Interval for Precipitations

  • 95% Confidence Interval: [491.96 mm, 663.58 mm]
  • Margin of Error: 85.81 mm
This interval is supposed to contain approximately 95% of the precipitation data. Let's calculate the actual percentage of data within this interval to verify.

Summary of Precipitation Data Analysis

  • 95% Confidence Interval: [491.96 mm, 663.58 mm]
  • Margin of Error: 85.81 mm
  • Actual Percentage of Data Within Interval: 32.65%
Observation: The calculated confidence interval does not contain 95% of the data as expected, but only about 32.65%. This discrepancy suggests that the distribution of precipitation may not be normal or there could be other influencing factors.

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