A random sample of tweets made by the @AucklandUni Twitter account were used to create the data set below. Use the data set above to decide if each of the following statements are TRUE or FALSE. The variable tweet_id will be identified as numeric by iNZight Lite but it doesn't really make much sense to use it as such for analysis like calculating averages. TRUE The variable year_tweeted could be converted to a categorical variable as part of analysis. [选择] FALSE TRUE The variable contains_link will be identified as a categorical variable by iNZight Lite. [选择] TRUE FALSE The data set displayed above is rectangular. [选择] TRUE FALSEMultiple dropdown selections
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A random sample of tweets made by the @AucklandUni Twitter account were used to create the data set below. Use the data set above to decide if each of the following statements are TRUE or FALSE. The variable number_retweets will be identified as a numeric variable by iNZight Lite. [选择] FALSE TRUE The variable number_likes will be identified as a categorical variable by iNZight Lite. [选择] FALSE TRUE The variable contains_link will be identified as a categorical variable by iNZight Lite. TRUE The data set displayed above is rectangular. TRUE
A random sample of tweets made by the @AucklandUni Twitter account were used to create the data set below. Use the data set above to decide if each of the following statements are TRUE or FALSE. The variable number_characters will be identified as a numeric variable by iNZight Lite. TRUE The variable tweet_length will be identified as a numeric variable by iNZight Lite. [选择] TRUE FALSE The variable year_tweeted will be identified as a categorical variable by iNZight Lite. FALSE The data set displayed above is rectangular. [选择] TRUE FALSE
[table] Property Type | Location | No of bedrooms | Internal Size | Price Sold | Total income 1 | 2 | 2 | 71 | $ 870,812.30 | $ 93,000 3 | 3 | 2 | 79.2 | $ 881,708.10 | $ 198,000 2 | 5 | 2 | 104.4 | $ 849,032.10 | $ 107,000 2 | 1 | 3 | 114 | $ 1,747,566.00 | $ 499,000 3 | 5 | 2 | 77 | $ 476,867.30 | $ 91,000 [/table] [table] Descriptions | Property Type: | Location: 1 = Apartment | 1 = Eastern suburbs 2 = House | 2 = Northern suburbs 3 = Townhouse | 3 = Sydney CBD 4 = Villa | 4 = Western suburbs 5 = Other | 5 = Southern suburbs [/table]Property type is a/an _________ variable
[table] Property Type | Location | No of bedrooms | Internal Size | Price Sold | Total income 1 | 2 | 2 | 71 | $ 870,812.30 | $ 93,000 3 | 3 | 2 | 79.2 | $ 881,708.10 | $ 198,000 2 | 5 | 2 | 104.4 | $ 849,032.10 | $ 107,000 2 | 1 | 3 | 114 | $ 1,747,566.00 | $ 499,000 3 | 5 | 2 | 77 | $ 476,867.30 | $ 91,000 [/table][table] Descriptions | Property Type: | Location: 1 = Apartment | 1 = Eastern suburbs 2 = House | 2 = Northern suburbs 3 = Townhouse | 3 = Sydney CBD 4 = Villa | 4 = Western suburbs 5 = Other | 5 = Southern suburbs [/table]Internal size is a/an _________ variable.
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