In 2023, the violent crime rate in the United States was at 374.4 cases per 100,000 inhabitants. However, the total rate of property crime was far higher, at 1,916.7 cases per 100,000 inhabitants.

Reading 017, Surrey full crime rankings and individual crime statistics updated monthly. See how safe Reading 017, Surrey is as well as all recent crimes.

Summary: By Breyon SturdivantStorymap metadata page: URL forthcoming Possible K-12 Next Generation Science standards addressed:Grade level(s) 6-8: Standard MS-LS1-5 - From Molecules to Organisms: Structures and Processes - Construct a scientific explanation based on evidence for how environmental and genetic factors influence the growth of organismsGrade level(s) 6-8: Standard MS-ESS3-4 - Earth and Human Activity - Construct an argument supported by evidence for how increases in human population and per-capita consumption of natural resources impact Earth’s systemsGrade level(s) 6-8: Standard MS-ESS3-5 - Earth and Human Activity - Ask questions to clarify evidence of the factors that have caused the rise in global temperatures over the past centuryGrade level(s) 9-12: Standard HS-ESS2-7 - Earth’s Systems - Construct an argument based on evidence about the simultaneous coevolution of Earth’s systems and life on EarthMost frequently used words:crimepovertyrateschicagocityApproximate Flesch-Kincaid reading grade level: 9.5. The FK reading grade level should be considered carefully against the grade level(s) in the NGSS content standards above.

Reading West, Arun property and local residence statistical data. View in-depth data for Reading West & surrounding areas.

The statistic shows a distribution of crime/mystery book readers across age groups in the United States in the first quarter of 2014. Mystery fiction had the largest popularity (** percent) among readers aged 65 or older.

AUSTIN POLICE DEPARTMENT DATA DISCLAIMER Please read and understand the following information. This dataset contains a record of incidents that the Austin Police Department responded to and wrote a report. Please note one incident may have several offenses associated with it, but this dataset only depicts the highest level offense of that incident. Data is from 2003 to present. This dataset is updated weekly. Understanding the following conditions will allow you to get the most out of the data provided. Due to the methodological differences in data collection, different data sources may produce different results. This database is updated weekly, and a similar or same search done on different dates can produce different results. Comparisons should not be made between numbers generated with this database to any other official police reports. Data provided represents only calls for police service where a report was written. Totals in the database may vary considerably from official totals following investigation and final categorization. Therefore, the data should not be used for comparisons with Uniform Crime Report statistics. The Austin Police Department does not assume any liability for any decision made or action taken or not taken by the recipient in reliance upon any information or data provided. Pursuant to section 552.301 (c) of the Government Code, the City of Austin has designated certain addresses to receive requests for public information sent by electronic mail. For requests seeking public records held by the Austin Police Department, please submit by utilizing the following link: https://apd-austintx.govqa.us/WEBAPP/_rs/(S(0auyup1oiorznxkwim1a1vpj))/supporthome.aspx

The statistic shows a distribution of crime/mystery book readers across genders in the United States in the first quarter of 2014. Clearly, with a ** percent result, women had a larger share of the genre's audience.

Reading 015, Ealing property and local residence statistical data. View in-depth data for Reading 015 & surrounding areas.

Reading 008, Norfolk property and local residence statistical data. View in-depth data for Reading 008 & surrounding areas.

ALLBUScompact is offered as an alternative to the structurally more complex full version of ALLBUS. It addresses the needs of newcomers to data analysis by providing a simplified demography module containing an easily manageable group of the most important demographic indicators. All topical question modules not containing sensitive data are retained as in the ALLBUS full version (scientific use file).

Topics:

1.) Use of media: Frequency and average total time of watching tv, frequency of watching news programs on public and commercial tv, frequency of reading a daily newspaper per week, frequency of reading books / e-books; internet use: frequency and type of device, frequency of using social media for political information, trustworthiness of different news sources with regard to crime and public safety.

2.) Social Inequality: Self-assessment of social class, fair share in standard of living, assessment of access to education, attitudes towards social inequality and the welfare state.

3.) Ethnocentrism and minorities: Attitude towards the influx of various groups of immigrants, attitudes towards the foreigners living in Germany, contacts with foreigners, antisemitic stereotypes and prejudices, attitudes towards Islam (Islamophobia), perceived risks and chances with respect to refugees.

4.) Family and gender roles: Attitudes towards working fathers and mothers, division of labor regarding house and family work., importance of educational goals.

5.) Values: Work orientations, attitudes towards legalizing abortion, materialism / postmaterialism (importance of law and order, fighting rising prices, free expression of opinions and influence on governmental decisions).

6.) Political attitudes: Pride in being a German, confidence in public institutions and organizations (public health service, federal constitutional court, federal parliament (Bundestag), city or municipal administration, churches, judiciary, television, newspapers, universities, federal government, the police, political parties, European Commission, European Parliament); identification with own community, the Federal Republic of Germany and the EU, preference for lower taxes or more social spending, stance on extension or reduction in social services, perceived strength of conflicts between social groups, political interest, self-placement on left-right continuum, satisfaction with democracy in Germany, voting intention (Sonntagsfrage).

7.) Deviant behavior and sanctions: Assessment of adequacy of court decisions, development of crime rate, moral assessment of deviant acts, crime-specific desire for sanctions (punitivity), desire to prohibit specific behaviors, attitude towards the death penalty, self-reported deviant behavior (past and future), perceived risk of being caught committing various crimes, victimisation (theft, any crime), respect of the law (norm), deterring crime through punishment, purpose of punishment, self-control (Grasmick), fear of crime, feeling of safety in living environment.

8.) Health: Self-assessment of overall health, physical and mental health during the last four weeks, acceptance of state powers to control epidemics.

9.) Religion: Self-assessment of religiousness, denomination, frequency of church attendance / attending a house of God.

10.) Other topics: Assessment of the present and future economic situation in Germany, assessment of present and future personal economic situation, social pessimism and orientation towards the future (anomia), interpersonal trust, reciprocity, authoritarianism, overall life satisfaction.

11.) ALLBUS-Demography: Details about the respondent: age, gender, marital status, citizenship (nationality), school education, vocational training, employment status, affiliation to public service, working hours per week (primary and secondary job), supervisory functions, fear of unemployment, length of unemployment, status of non-employment, date of termination of full-time employment, current or former membership in a trade union, membership in a political party, respondent´s income. Place of residence (size of municipality), duration of residence (in Germany and at current place of residence), mobility.

Details about respondent´s current spouse: age, school education, vocational training, employment status, affiliation to public service, status of non-employment.

Details about respondent´s steady partner: age, school education, vocational training, employment status, affiliati...

Reading 020, Hampshire property and local residence statistical data. View in-depth data for Reading 020 & surrounding areas.

In 2024, the most common type of cybercrime reported to the United States internet Crime Complaint Center was phishing, with its variation, spoofing, affecting approximately 193,000 individuals. In addition, over 86,000 cases of extortion were reported to the IC3 during that year. Dynamic of phishing attacks Over the past few years, phishing attacks have increased significantly. In 2024, over 193,000 individuals fell victim to such attacks. The highest number of phishing scam victims since 2018 was recorded in 2021, approximately 324 thousand.Phishing attacks can take many shapes. Bulk phishing, smishing, and business e-mail compromise (BEC) are the most common types. With the recent development of generative AI, it has become easier to craft a believable phishing e-mail. This is currently among the top concerns of organizations leaders. Impact of phishing attacks Among the most targeted industries by cybercriminals are healthcare, financial, manufacturing, and education institutions. An observation carried out in the fourth quarter of 2024 found that software-as-a-service (SaaS) and webmail was most likely to encounter phishing attacks. According to the reports, almost a quarter of them stated being targeted by a phishing scam in the measured period.

Version 9 release notes:Adds 2022 dataVersion 8 release notes:Fixes issue where 2021 Property Segment data was excluded. Thank you to Uriel Lomeli for telling me about this issue.Version 7 release notes:Adds 2021 data.Version 6 release notes:Adds batch header segments for all years. Version 5 release notes:Adds 2020 dataVersion 4 release notes:Fix bug where most years had arrestee and property were incorrectly window arrestee and window property segments.Changes R files from .rda to .rds.Version 3 release notes:Adds 2019 dataVersion 2 release notes:Changes release notes description, does not change data.These data are the FBI's National Incident-Based Reporting System (NIBRS) data for years 1991-2018. NIBRS data are incident-level data that have highly detailed information for each crime that is reported to the police agency. This data has 10 segments. Each segment has different data about the crime. AdministrativeBasic information about the crime incident - this is basically metadata about the other segments for this crime. This includes the date of the crime, the number of offense segments, the number of victim segments, the number of offender segments, the number of arrestee segments, if the crime was cleared exceptionally and (if it was) what date it was cleared. ArresteeArrestee-level information for those who are arrested. This includes demographics (age, sex, race, ethnicity), the date of the arrest (can be different than the date of the crime), what weapon (if any) was used, and the outcome of the case if the arrestee was a juvenile. Group B Arrest ReportsArrestee-level information for those who are arrested for Group B crimes. This includes the same variables as the arrestee segment. OffenderOffender-level information for each offender. Includes offender demographics (age, sex, race, ethnicity).OffenseDetailed information about each crime. Includes the weapon used (if any), the location of the crime, if the offender was intoxicated (including drugs and alcohol), and what their bias motivation (if any) was (if there is one, this would be considered a hate crime). PropertyInformation about property involved in the crime (i.e. drugs or stolen property). This includes the value of the property, what type of the property it was, when it was recovered. For drugs, this includes the drug and its quantity. VictimVictim-level information for each victim of a crime. Includes victim demographics (age, sex, race, ethnicity), injury, and relationship to the offender(s).Window ArresteeWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Window Exceptional ClearanceWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Window PropertyWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Due to the large file size, each year is its own file. All segment headers are available except for the batch headers. What I did here was read the data into R and save it as R and Stata files. No other changes to the data were made. The data was downloaded as NIBRS Master Files for each year from the FBI's Crime Data Explorer website - https://crime-data-explorer.fr.cloud.gov/downloads-and-docs.

In 2022/23, the proportion of all adult offenders who reoffended in England and Wales was 26 percent. Since 2008/09 the reoffending rate has fluctuated between a high of 31.6 percent in 2008/09 to a low of 24 percent in 2020/21.