A random sample of tweets made by @AucklandUni was obtained. Load the dataset into iNZight Lite using this link and produce relevant summary statistics to answer the questions below. Note: When you are using two categorical variables, the order you put variables into iNZight Lite does affect the frequency table in the summary so consider this carefully. Give your answers as percentages rounded to one decimal place e.g. 23.1% or 42.0%. What proportion of the tweets were tweeted in the afternoon or evening (PM)?[Fill in the blank] % What proportion of the tweets had between 150 and 200 characters?[Fill in the blank] % Of the tweets that were tweeted in the morning (AM), what proportion had between 150 and 200 characters?[Fill in the blank] % Of the tweets that had more than 200 characters, what proportion were tweeted in the afternoon or evening (PM)?[Fill in the blank] % Multiple fill-in-the-blank

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A random sample of tweets made by @AucklandUni were used to explore whether engagement with a tweet could be predicted based on characteristics of the tweet. The plots below were constructed using iNZight Lite and two of the variables created from the tweets. Use the plots above to decide if each of the following statements are TRUE or FALSE. Around 24% of the tweets received no likes. [选择] TRUE FALSE Most of the tweets contained no links. [选择] TRUE FALSE Of the tweets that contain no links, around 26% received no likes. [选择] TRUE FALSE Knowing that the tweet contains a link appears to be very helpful for predicting whether the tweet will receive likes. [选择] FALSE TRUE

A random sample of tweets made by @AucklandUni were used to explore whether engagement with a tweet could be predicted based on characteristics of the tweet. The plots below were constructed using iNZight Lite and two of the variables created from the tweets. Use the plots above to decide if each of the following statements are TRUE or FALSE. Around 29% of the tweets received no retweets. [选择] FALSE TRUE Most of the tweets had more than 140 characters. FALSE Of the tweets that had more than 140 characters, around 30% received no retweets. [选择] TRUE FALSE Knowing how long the tweet is appears to be very helpful for predicting whether the tweet will be retweeted. [选择] TRUE FALSE

A random sample of tweets made by @AucklandUni were used to explore whether engagement with a tweet could be predicted based on characteristics of the tweet. The plots below were constructed using iNZight Lite and two of the variables created from the tweets. Use the plots above to decide if each of the following statements are TRUE or FALSE. Around 74% of the tweets received at least one like. [选择] TRUE FALSE Most of the tweets contained no links. [选择] TRUE FALSE Of the tweets that contain no links, around 29% received at least one like. TRUE Knowing that the tweet contains a link appears to be very helpful for predicting whether the tweet will receive likes. [选择] TRUE FALSE

A random sample of tweets made by @AucklandUni was obtained. Load the dataset into iNZight Lite using this link and produce relevant summary statistics to answer the questions below. Note: When you are using two categorical variables, the order you put variables into iNZight Lite does affect the frequency table in the summary so consider this carefully. Give your answers as percentages rounded to one decimal place e.g. 23.1% or 42.0%. What proportion of the tweets were tweeted in the morning (AM)?[Fill in the blank] % What proportion of the tweets had between 50 and 100 characters?[Fill in the blank] % Of the tweets that were tweeted in the afternoon or evening (PM), what proportion had between 150 and 200 characters?[Fill in the blank] % Of the tweets that had between 50 and 100 characters, what proportion were tweeted in the morning (AM)?[Fill in the blank] %

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